Predicting human developmental toxicity of pharmaceuticals using human stem-like cells and metabolomic ratios

ABSTRACT

This present invention provides rapid, reproducible, biomarker-based screening methods for the developmental toxicity testing of compounds. The methods are designed to identify the exposure level at which a test compound perturbs metabolism in a manner predictive of developmental toxicity. In particular, the perturbation of two metabolites, ornithine and cystine, is measured, wherein a ratio of the fold change in ornithine to the fold change in cystine of less than or equal to about 0.88 is indicative of the teratogenicity of a test compound.

CONTINUING APPLICATION DATA

This application claims the benefit of U.S. Provisional Application Ser.No. 61/721,746, filed Nov. 2, 2012, and Ser. No. 61/827,407, filed May24, 2013, each of which is incorporated by reference herein.

GOVERNMENT FUNDING

This invention was made with government support under Grant No.IIP-1058355, awarded by the National Science Foundation. The Governmenthas certain rights in the invention.

BACKGROUND

Birth defects are reported in approximately 3% of all human births andare the largest cause of infant mortality in the United States (Hoyertet al., 2006, Pediatrics; 117:168-183). Exposure to toxic chemicals andphysical agents is believed to be responsible for approximately 3% ofall birth defects (National Research Council, 2000, “Scientificfrontiers in developmental toxicology and risk assessment,” Washington,D.C.: The National Academies Press).

It is understood that developmental toxicity can cause birth defects,and can generate embryonic lethality, intrauterine growth restriction(IUGR), dysmorphogenesis (such as skeletal malformations), andfunctional toxicity, which can lead to cognitive disorders such asautism. There is an increasing concern about the role that chemicalexposure can play in the onset of these disorders. Indeed, it isestimated that 5% to 10% of all birth defects are caused by in uteroexposure to known teratogenic agents that induce developmentalabnormalities in the fetus (Beckman and Brent, 1984, Annu Rev Pharmacol;24: 483-500). Concern exists that chemical exposure may be playing asignificant and preventable role in producing birth defects (Claudio etal., 2001, Environm Health Perspect; 109: A254-A261).

However, this concern has been difficult to evaluate, due to the lack ofrobust and efficient models for testing developmental toxicity for themore than 80,000 chemicals in the market, plus the new 2,000 compoundsintroduced annually (General Accounting Office (GAO), 1994, ToxicSubstances Control Act: Preliminary Observations on Legislative Changesto Make TSCA More Effective, Testimony, Jul. 13, 1994,GAO/T-RCED-94-263). Fewer than 5% of these compounds have been testedfor reproductive outcomes and even fewer for developmental toxicity(Environmental Protective Agency (EPA), 1998, Chemical Hazard DataAvailability Study, Office of Pollution Prevention and Toxins). Althoughsome attempts have been made to use animal model systems to assesstoxicity (Piersma, 2004, Toxicology Letters; 149:147-53), inherentdifferences in the sensitivity of humans in utero have limited thepredictive usefulness of such models.

Toxicity, particularly developmental toxicity, is also a major obstaclein the progression of compounds through the drug development process.Currently, toxicity testing is conducted on animal models as a means topredict adverse effects of compound exposure, particularly ondevelopment and organogenesis in human embryos and fetuses. The mostprevalent models that contribute to FDA approval of investigational newdrugs are whole animal studies in rabbits and rats (Piersma, 2004,Toxicology Letters; 149: 147-53). In vivo studies rely on administrationof compounds to pregnant animals at different stages of pregnancy andembryonic/fetal development (first week of gestation, organogenesisstage and full gestation length). However, these in vivo animal modelsare limited by a lack of biological correlation between animal and humanresponses to chemical compounds during development due to differences inbiochemical pathways. Species differences are often manifested in trendssuch as dose sensitivity and pharmacokinetic processing of compounds.According to the reported literature, animal models are approximately60% efficient in predicting human developmental response to compounds(Greaves et al., 2004, Nat Rev Drug Discov; 3:226-36). Thus, there is aneed for human-directed predictive in vitro models.

The thalidomide tragedy in the 1960s emphasized the importance ofpreclinical developmental toxicity testing, the significant differencesamong species in their response to potentially teratogenic compounds,and how the developing fetus can be affected by such compounds.Developmental toxicity testing of thalidomide in rodent models did notindicate the compound's teratogenic potential in humans. Over 10,000children were born with severe birth defects following in uteroexposure. Current preclinical models for detecting developmentaltoxicity have varying degrees of concordance with observed developmentaltoxicity in humans, with rats and rabbits (the most commonly usedspecies for developmental toxicity testing) having approximately 70-80%concordance to known human teratogens (Daston G P and Knudsen T B, 2010,“Fundamental concepts, current regulatory design and interpretation,”In: Knudsen T B, Daston G P, editors. Comprehensive Toxicology. Vol 12,2nd ed. New York: Elsevier. p 3-9). These decades-old in vivo animalmodels require large numbers of animals, kilogram quantities of testcompound, and are both time consuming and expensive. Due to the cost andcomplexity of these models, safety assessments often occur too late inthe compound's life cycle for the developer to react to a positivedevelopmental toxicity signal, and can result in the termination of thedevelopment of the compound or series. Though these animal models are,and have long been, considered the regulatory gold standard, differencesin species response to a compound may lead to missed signals ofdevelopmental toxicity and biological misinterpretation. As such, thedevelopment of a new generation of tools using human cells forassessment of potential developmental toxicity risk related to chemicalexposure is needed. The appropriate tests would also reduce productdevelopment time, control costs, and respond proactively to the call todecrease animal use.

Thus, there is a need for a relevant, predictive, accurate, low cost,and rapid human in vitro tests for reliably determining developmentaltoxicity of pharmaceutical agents and other chemical compounds.

SUMMARY OF THE INVENTION

The present invention includes a method of classifying a test compoundas a teratogen or a non-teratogen, the method including culturingundifferentiated human stem cell-like cells (hSLCs) in the presence ofthe test compound and in the absence of the test compound; determiningthe fold change in ornithine, or fragment, adduct, deduct or lossthereof, in the culture media of undifferentiated hSLCs cultured in thepresence of the test compound in comparison with hSLCs cultured in theabsence of the test compound; determining the fold change in cystine, orfragment, adduct, deduct or loss thereof, in the culture media ofundifferentiated hSLCs cultured in the presence of the test compound incomparison with hSLCs cultured in the absence of the test compound; anddetermining the ratio of the fold change in ornithine, or fragment,adduct, deduct or loss thereof, to the fold change in cystine, orfragment, adduct, deduct or loss thereof, wherein a ratio of less thanor equal to about 0.88 is indicative of the teratogenicity of the testcompound and a ratio of greater than about 0.88 is indicative of thenon-teratogenicity of the test compound.

The present invention includes a method of predicting teratogenicity ofa test compound, the method including culturing undifferentiated humanstem cell-like cells (hSLCs) in the presence of the test compound and inthe absence of the test compound; determining the fold change inornithine, or fragment, adduct, deduct or loss thereof, in the culturemedia of undifferentiated hSLCs cultured in the presence of the testcompound in comparison with hSLCs cultured in the absence of the testcompound; determining the fold change in cystine, or fragment, adduct,deduct or loss thereof, in the culture media of undifferentiated hSLCscultured in the presence of the test compound in comparison with hSLCscultured in the absence of the test compound; and determining the ratioof the fold change in ornithine, or fragment, adduct, deduct or lossthereof, to the fold change in cystine, or fragment, adduct, deduct orloss thereof, wherein a ratio of less than or equal to about 0.88 isindicative of the teratogenicity of the test compound and a ratio ofgreater than about 0.88 is indicative of the non-teratogenicity of thetest compound.

The present invention includes a method for validating a test compoundas a teratogen, the method including culturing undifferentiated humanstem cell-like cells (hSLCs) in the presence of the test compound and inthe absence of the test compound; determining the fold change inornithine, or fragment, adduct, deduct or loss thereof, in the culturemedia of undifferentiated hSLCs cultured in the presence of the testcompound in comparison with hSLCs cultured in the absence of the testcompound; determining the fold change in cystine, or fragment, adduct,deduct or loss thereof, in the culture media of undifferentiated hSLCscultured in the presence of the test compound in comparison with hSLCscultured in the absence of the test compound; and determining the ratioof the fold change in ornithine, or fragment, adduct, deduct or lossthereof, to the fold change in cystine, or fragment, adduct, deduct orloss thereof, wherein a ratio of less than or equal to about 0.88 isindicative of the teratogenicity of the test compound and a ratio ofgreater than about 0.88 is indicative of the non-teratogenicity of thetest compound.

The present invention includes a method for determining the exposureconcentration at which a test compound is teratogenic, the methodincluding culturing undifferentiated human stem cell-like cells (hSLCs)in a range of concentrations of the test compound and in the absence ofthe test compound; determining the fold change in ornithine, orfragment, adduct, deduct or loss thereof, in the culture media ofundifferentiated hSLCs cultured in each concentration of the testcompound in comparison with hSLCs cultured in the absence of the testcompound; determining the fold change in cystine, or fragment, adduct,deduct or loss thereof, in the culture media of undifferentiated hSLCscultured in each concentration of the test compound in comparison withhSLCs cultured in the absence of the test compound; and determining theratio of the fold change in ornithine, or fragment, adduct, deduct orloss thereof, to the fold change in cystine, or fragment, adduct, deductor loss thereof, for each concentration of test compound, wherein aratio of less than or equal to about 0.88 at a given concentration ofthe test compound is indicative of the teratogenicity of the testcompound at that given concentration and a ratio of greater than about0.88 at a given concentration of the test compound is indicative of thenon-teratogenicity of the test compound at that given concentration.

In some aspects of the methods of the present invention, cystine, orfragment, adduct, deduct or loss thereof, and/or ornithine, or fragment,adduct, deduct or loss thereof, are identified using a physicalseparation method. In some aspects, a physical separation methodincludes mass spectrometry. In some aspects, mass spectrometry includesliquid chromatography/electrospray ionization mass spectrometry.

In some aspects of the methods of the present invention, cystine, orfragment, adduct, deduct or loss thereof, and/or ornithine, or fragment,adduct, deduct or loss thereof, are measured using a colorimetric orimmunological assay.

In some aspects of the methods of the present invention, hSLCs includeshuman embryonic stem cells (hESCs), human induced pluripotent (iPS)cells, or human embryoid bodies.

In some aspects of the methods of the present invention, the hSLCs arecultured at a concentration of the test compound including the testcompound's human therapeutic Cmax.

In some aspects of the methods of the present invention, the hSLCs arecultured in a range of concentrations of the test compound. In someaspects, the range of concentrations includes a serial dilution. In someaspects, the range of concentrations includes nine three-fold dilutions.In some aspects, the range of concentrations includes from about 0.04 μMto about 300 μM, about 4 μM to about 30,000 μM, and about 0.0001 μM toabout 10μ. In some aspects, the range of concentrations of the testcompound includes the test compound's human therapeutic Cmax.

In some aspects of the methods of the present invention, the methodfurther includes detecting one or more additional metabolites associatedwith hSLCs cultured in the presence of the test compound in comparisonwith hSLCs cultured in the absence of the test compound. In someaspects, one or more additional metabolite includes arginine, ADMA,cystathionine, and/or a fragment, adduct, deduct or loss thereof. Insome aspects, one or more additional metabolites are identified using aphysical separation method. In some aspects, a physical separationmethod includes mass spectrometry. In some aspects, mass spectrometryincludes liquid chromatography/electrospray ionization massspectrometry. In some aspects, one or more additional metabolites aremeasured using a colorimetric or immunological assay.

In some aspects of the methods of the present invention, the methodfurther includes determining the ratio of the fold change in arginine,or fragment, adduct, deduct or loss thereof, to the fold change in ADMA,or fragment, adduct, deduct or loss thereof, wherein a ratio of lessthan at least about 0.9 or greater than at least about 1.1 is indicativeof the teratogenicity of the test compound and a ratio of greater thanat least about 0.9 and less than at least about 1.1 is indicative of thenon-teratogenicity of the test compound.

The term “and/or” means one or all of the listed elements or acombination of any two or more of the listed elements.

The words “preferred” and “preferably” refer to embodiments of theinvention that may afford certain benefits, under certain circumstances.However, other embodiments may also be preferred, under the same orother circumstances. Furthermore, the recitation of one or morepreferred embodiments does not imply that other embodiments are notuseful, and is not intended to exclude other embodiments from the scopeof the invention. The embodiment(s) described, and references in thespecification to “one embodiment,” “an embodiment of the invention,” “anembodiment,” “an example embodiment,” etc., indicate that theembodiment(s) described may include a particular feature, structure, orcharacteristic, but every embodiment may not necessarily include theparticular feature, structure, or characteristic. Moreover, such phrasesare not necessarily referring to the same embodiment. Further, when aparticular feature, structure, or characteristic is described inconnection with an embodiment, it is understood that it is within theknowledge of one skilled in the art to effect such feature, structure,or characteristic in connection with other embodiments whether or notexplicitly described.

The terms “comprises” and variations thereof do not have a limitingmeaning where these terms appear in the description and claims. It isunderstood that wherever embodiments are described herein with thelanguage “comprising,” otherwise analogous embodiments described interms of “consisting of” and/or “consisting essentially of” are alsoprovided.

Unless otherwise specified, “a,” “an,” “the,” and “at least one” areused interchangeably and mean one or more than one.

In the following description, for purposes of explanation, specificnumbers, parameters and reagents are set forth in order to provide athorough understanding of the invention. It is understood, however, thatthe invention can be practiced without these specific details. In someinstances, well-known features can be omitted or simplified so as not toobscure the present invention.

Also herein, the recitations of numerical ranges by endpoints includeall numbers subsumed within that range (e.g., 1 to 5 includes 1, 1.5, 2,2.75, 3, 3.80, 4, 5, etc.).

Unless otherwise indicated, all numbers expressing quantities ofcomponents, molecular weights, and so forth used in the specificationand claims are to be understood as being modified in all instances bythe term “about.” Accordingly, unless otherwise indicated to thecontrary, the numerical parameters set forth in the specification andclaims are approximations that may vary depending upon the desiredproperties sought to be obtained by the present invention.

For any method disclosed herein that includes discrete steps, the stepsmay be conducted in any feasible order. And, as appropriate, anycombination of two or more steps may be conducted simultaneously.

The above summary of the present invention is not intended to describeeach disclosed embodiment or every implementation of the presentinvention. The description that follows more particularly exemplifiesillustrative embodiments. In several places throughout the application,guidance is provided through lists of examples, which examples can beused in various combinations. In each instance, the recited list servesonly as a representative group and should not be interpreted as anexclusive list.

BRIEF DESCRIPTION OF THE FIGURES

FIGS. 1A and 1B. Plate design for untargeted metabolomics treated atsingle exposure levels used in Phase 1 experiments (FIG. 1A) andtargeted biomarker experiments treated at multiple exposure levels usedfor Phase 2 experiments (FIG. 1B). Both plates incorporate a referencedesign where the experimental control or reference treatment (0.1% DMSO)is present on each plate. Media only (lacking cells) controls are usedto assess the impact of the test compounds on the sample matrix. Eachwell is analyzed as an individual sample. Filled circles represent cellsamples and filled squares depict media control samples.

FIG. 2. Graphical representation of the targeted biomarker assay. Humanembryonic stem (hES) cells were exposed to nine concentrations of a testcompound that spanned four log units. The dose response curve for theornithine/cystine ratio (o/c ratio; grey curve) and cell viability(black curve) was fit using a four-parameter log-logistic model. Theconcentration predicted by the interpolated point where the doseresponse curve of the o/c ratio crosses the teratogenicity threshold(0.88; grey line) indicates the exposure level where a metabolicperturbation has teratogenic potential (i.e., teratogenicity potential:o/c ratio, open circle). The teratogenicity potential concentration fromcell viability (filled circle) is the interpolated point where the cellviability dose response curve exceeds the teratogenicity threshold. Theteratogenicity potential creates a two-sided toxicity model based onexposure: one where exposure does not perturb metabolism in a mannerassociated with teratogenicity (lighter shaded box) and another whereexposure may cause a potentially teratogenic shift in metabolism (darkershaded box). The x-axis is the concentration (μM) of the compound. Boththe cell viability measurements and o/c ratio measurements exist on thesame scale represented by Δ on the y-axis. The y-axis value of the o/cratio is the ratio of the reference treatment normalized (fold change)values (ornithine/cystine). The y-axis value of the viabilitymeasurement is the treatment cell viability RFU normalized to thereference treatment cell viability RFU.

FIGS. 3A and 3B. Graphical representation of the classification schemefor known human teratogens and non-teratogens utilizing the therapeuticC_(max) concentration to set the classification windows. The doseresponse curve for the o/c ratio (grey curve) was fit using afour-parameter log-logistic model and used to interpolate theconcentration where the o/c ratio crosses the teratogenicity threshold(i.e., teratogenicity potential, open circle). A test compound waspredicted as a non-teratogen when the teratogenicity potentialconcentration is higher than the human therapeutic C_(max) (FIG. 3A). Atest compound was predicted as a teratogen when the teratogenicitypotential concentration is lower than the human therapeutic C_(max)(FIG. 3B). The same logic outlined here is also applied to the viabilitymeasurements. The x-axis is the concentration (μM) of the compound. They-axis value of the o/c ratio is the ratio of the reference treatmentnormalized (fold change) values (ornithine/cystine).

FIGS. 4A, 4B, and 4C. Metabolic perturbation of ornithine (FIG. 4A),cystine (FIG. 4B), and the o/c ratio (FIG. 4C) measured in experimentalPhase 1. Each point represents the mean value of the 9 independentexperimental blocks. Filled points indicate teratogens and open pointsindicate non-teratogens. Error bars are the standard error of the mean.The vertical grey line(s) represent the teratogenicity threshold. Thex-axis is the reference normalized fold change of each metabolite (FIGS.4A and 4B) or the ratio of ornithine/cystine reference normalized values(FIG. 4C). The y-axis is the treatment ordered by non-teratogens andteratogens. Open arrows indicate range where a compound would beclassified as a non-teratogen. Filled arrows indicate the range where acompound would be classified as a teratogen.

FIGS. 5A and 5B. Visualization of the difference between a compound'steratogenicity potential concentration for the o/c ratio (TP) determinedin Phase 2 and C_(max) values from the targeted biomarker assay for thetraining set (FIG. 5A) and test set (FIG. 5B). Filled points correspondto teratogens and open points correspond to non-teratogens. Treatmentsthat have a difference between the TP and C_(max) less than 0 areclassified as teratogens and treatments with a difference between the TPand C_(max) greater than 0 are classified as non-teratogens. The x-axisis the log base 10 transformed teratogen potential concentration valuesubtracted from the log base 10 transformed C_(max) concentration value(see Tables 6 and 7). The y-axis is the treatment ordered bynon-teratogens and teratogens. Open arrows indicate the range where acompound would be classified as a non-teratogen. Filled arrows indicatethe range where a compound would be classified as a teratogen. ¹TheC_(max) for everolimus is below the lowest exposure level used in theassay, the o/c ratio for this compound begins below the teratogenicitythreshold, so it is classified as a teratogen.

FIGS. 6A to 6F. Targeted biomarker assay results for a representativesubset of the training set compounds (Table 6). The dose response curvesfor the viability analysis (black curve) and o/c ratio (grey curve) areshown for 4 known human teratogens: thalidomide (FIG. 6A), all-transretinoic acid (FIG. 6B), valproic acid (FIG. 6C), 5-fluorouracil (FIG.6D), and 2 non-teratogens: retinol (FIG. 6E) and saccharin (FIG. 6F).The x-axis is the concentration (μM) of the compound. Both the cellviability measurements and o/c ratio measurements exist on the samescale represented by Δ on the y-axis. The y-axis value of the o/c ratiois the ratio of the reference treatment normalized (fold change) values(ornithine/cystine). The y-axis value for the viability measurement isthe treatment cell viability RFU normalized to the reference treatmentcell viability RFU. The vertical broken black line indicates thecompound specific C_(max) and the horizontal grey line indicates theteratogenicity threshold (0.88). The open circle represents theteratogen potential concentration (TP) for the o/c ratio. The lighterand darker shaded areas represent the concentrations where the compoundis predicted to be non-teratogenic or teratogenic, respectively. Thepoints are mean values and error bars are the standard error of themean. Interpretation of these figures is outlined in FIGS. 2 and 3.

FIGS. 7A and 7B. Targeted biomarker assay results compared to rat invivo developmental toxicity outcomes for two test set compounds (Table7): lovastatin (FIG. 7A) and lapatinib (FIG. 7B). The dose responsecurves from the targeted biomarker assay for the viability analysis(black line) and o/c ratio (grey line) are shown. The x-axis is theconcentration (μM) of the compound. Both the cell viability measurementsand o/c ratio measurements exist on the same scale represented by Δ onthe y-axis. The y-axis value of the o/c ratio is the ratio of thereference treatment normalized (fold change) values (ornithine/cystine).The y-axis value for the viability measurement is the treatment cellviability RFU normalized to the reference treatment cell viability RFU.The vertical broken black line indicates the compound specific C_(max)and the horizontal grey line indicates the teratogenicity threshold(0.88). The open circle represents the teratogen potential concentration(TP) for the o/c ratio. The lighter and darker shaded areas representthe concentrations where the compound is predicted to be non-teratogenicor teratogenic, respectively. The broken grey line represents theconcentration where a positive result was observed in the rat in vivodevelopmental toxicity test. The points are mean values and error barsare the standard error of the mean. Interpretation of these figures isoutlined in FIGS. 2 and 3.

FIG. 8. Diagram outlining the development of the targeted biomarkerassay compared to use with unknown compounds.

FIG. 9 shows the ratio of the reference treatment normalized ratio ofADMA and cystine for each training set agent.

FIG. 10 shows the ratio of the reference treatment normalized ratio ofcystathionine and cystine for each training set agent.

DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

The present invention provides human-specific in vitro methods fordetermining toxicity, particularly developmental toxicity, andteratogenicity of pharmaceuticals and other non-pharmaceutical chemicalcompounds using human stem-like cells (hSLCs). The present inventionutilizes hSLCs and metabolomics to provide a predictive, quantitative,all-human in vitro screening method for predicting human developmentaltoxicity of compounds. The present methods overcome limitationsassociated with interspecies animal models and provide innovative androbust alternative in vitro model systems to predict developmentaltoxicity of chemicals. The application of more predictive developmentaltoxicity screens would reduce the prevalence of birth defects andincrease pharmaceutical and chemical safety.

The present invention provides an exposure-based in vitro assay bymeasuring a metabolic perturbation in the culture media that could beused as an early signal for the potential of developmental toxicity.

With the methods of the present invention, any of a variety of humanstem-like cells (hSLCs) may be used to predict developmental toxicity ofchemical entities. Human stem-like cells include, but are not limitedto, pluripotent, undifferentiated human embryonic stem cells (hESCs),human induced pluripotent (iPS) cells, human embryoid bodies, andhSLC-derived lineage-specific cells.

hESCs are pluripotent, self-renewing cells isolated directly frompreimplantation human embryos that recapitulate organogenesis in vitro.Lineage-specific precursor cells are derived from hESCs and have entereda specific cellular lineage, but yet remain multipotent with regard tocell type within that specific lineage. For example, neural precursorshave committed to neural differentiation but yet remain unrestricted asto its neural cell type. As used herein, the term “human embryonic stemcells (hESCs)” is intended to include undifferentiated stem cellsoriginally derived from the inner cell mass of developing blastocysts,and specifically pluripotent, undifferentiated human stem cells andpartially-differentiated cell types thereof (e.g., downstreamprogenitors of differentiating hESC). As provided herein, in vitrocultures of hESCs are pluripotent and not immortalized, and can beinduced to produce lineage-specific cells and differentiated cell typesusing methods well-established in the art. hESCs useful in the practiceof the methods of the present invention include, but are not limited to,those are derived from preimplantation blastocysts, for example, asdescribed by Thomson et al., in U.S. Pat. No. 6,200,806. Multiple hESClines are currently available in US and UK stem cell banks hESCs usedmay include any of the three hES cell lines, WA01, WA07, and WA09.Previous work has established that an untargeted metabolomics-basedevaluation of hES cell spent media following exposure to compounds withknown human teratogenicity outcomes produces predictive signatures thatcan be utilized as a developmental toxicity screen (Kleinstreuer et al.,2011, Toxicol Appl Pharmacol; 257:111-121; and West et al., 2010,Toxicol Appl Pharmacol; 247:18-27, each of which is incorporated hereinin its entirety).

Human induced pluripotent stem cells (iPS) cells are a type ofpluripotent stem cell artificially derived from a non-pluripotent cell,typically an adult somatic cell, by inducing a forced expression ofcertain genes. iPS cells are believed to be identical to naturalpluripotent stem cells, such as embryonic stem cells in many respects,such as the expression of certain stem cell genes and proteins,chromatin methylation patterns, doubling time, embryoid body formation,teratoma formation, viable chimera formation, and potency anddifferentiability. iPS cells may be obtained, for example, from adulttissues (such as for example, from cells obtained from the bone themarrow) and by parthenogenesis (see, for example, Vrana et al., 2003,Colloquium; 100, Supp. 1:11911-11916).

Human embryoid bodies are aggregates of cells derived from humanembryonic stem cells. Cell aggregation is imposed by hanging drop,plating upon non-tissue culture treated plates or spinner flasks; eithermethod prevents cells from adhering to a surface to form the typicalcolony growth. Upon aggregation, differentiation is initiated and thecells begin to a limited extent to recapitulate embryonic development.Embryoid bodies are composed of cells from all three germ layers:endoderm, ectoderm and mesoderm.

The cells of the present invention can include hSLC-derived lineagespecific cells. The terms “hSLC-derived lineage specific cells,”, “stemcell progenitor,” “lineage-specific cell,” “hSLC derived cell,” and“differentiated cell” as used herein are intended to encompasslineage-specific cells that are differentiated from hSLCs such that thecells have committed to a specific lineage of diminished pluripotency.For example, hSLC-derived lineage specific cells are derived from hSLCsand have entered a specific cellular lineage, but yet remain multipotentwith regard to cell type within that specific lineage. The hSLC-derivedlineage specific cells can include, for example, neural stem cells,neural precursor cells, neural cells, cardiac stem cells, cardiacprecursor cells, cardiomyocytes, and the like. In some embodiments,these hSLC-derived lineage-specific cells remain undifferentiated withregard to final cell type. For example, neuronal stem cells are derivedfrom hSLCs and have differentiated enough to commit to neuronal lineage.However, the neuronal precursor retains “stemness” in that it retainsthe potential to develop into any type of neuronal cell. Additional celltypes include terminally-differentiated cells derived from hESCs orlineage-specific precursor cells, for example neural cells.

With the methods of the present invention, hSLCs may be cultured usingmethods of cell culture well-known in the art, including, for example,methods disclosed in Ludwig et al. (2006, Nat Methods; 3:637-46), U.S.patent application Ser. No. 11/733,677 (“Reagents and Methods for UsingHuman Embryonic Stem Cells to Evaluate Toxicity of PharmaceuticalCompounds and other Compounds”), PCT/US2011/029471 and U.S. patentapplication Ser. No. 13/069,326 (“Predicting Human DevelopmentalToxicity of Pharmaceuticals Using Human Stem-Like Cells andMetabolomics”), and any of those described herein.

In some aspects of the present invention, hSLCs are maintained in anundifferentiated state prior to and/or during exposure to a testcompound. In some aspects of the present invention, hSLCs may becultured in the absence of a feeder cell layer during exposure to a testcompound and/or cultured on feeder cell layer prior to such exposure.

The methods of the present invention profile changes in cellularmetabolism that are measured in the spent cell culture medium from hSLCsfollowing compound exposure. This metabolic footprint of the culturemedium is a functional measurement of cellular metabolism referred to asthe “secretome.” The secretome refers to the metabolites present in thespent media (which may also be referred be herein as “cell culturesupernatant,” “culture supernatant,” “supernatant,” “cell supernatant,”“cell culture media,” “culture media,” “cell culture medium,” “culturemedium,” “media,” or “medium”) following cell culture. The secretomeincludes media components, metabolites passively and activelytransported across the plasma membrane, intracellular metabolitesrelease upon lysis, and those produced through extracellular metabolismof enzymes. The change in the secretome elicited by test compoundexposure relative to untreated cultures produces a metabolic signatureof toxicity. The secretome is measured because of several uniquequalities for profiling cell culture media; it is very easy toreproducibly sample, minimal handling is required to quench metabolism,it does not destroy the cells that can then be used for other assays, itis amenable to high-throughput evaluation, and strong signals can bemeasured due to the accumulation of metabolites over time. The abilityto measure metabolic changes following compound exposure has identifiednew biomarkers associated with disruption of human development andprovided the opportunity to develop highly predictive models ofdevelopmental toxicity based on these changes.

Metabolites include, but are not limited to, sugars, organic acids,amino acids, fatty acids, hormones, vitamins, oligopeptides (less thanabout 100 amino acids in length), as well as ionic fragments thereof. Insome aspects, metabolites are less than about 3000 Daltons in molecularweight, and more particularly from about 50 to about 3000 Daltons.

With the present invention, a fold change in a metabolite in hSLCscultured in the presence of a test compound in comparison with hSLCscultured in the absence of the teratogenic compound may be determined.The metabolic effect of a teratogenic compound refers to the differencein one or more metabolites in hSLCs cultured in presence of theteratogenic compound in comparison with hSLCs cultured in absence of theteratogenic compound (or, in some aspects, hSLCs cultured in presence ofa known non-teratogenic compound). A metabolite may be differentiallyexpressed, for example, the expression of a metabolite may be increasedor decreased when exposed to a teratogenic compound.

In some aspects, a ratio of the fold changes of two metabolites in hSLCscultured in presence of a test compound in comparison with hSLCscultured in absence of the teratogenic compound may be determined. Forexample, with the present invention, it has been determined that alteredratios in the fold changes of ornithine to cystine, asymmetricdimethylarginine (ADMA) to cystine, and/or cystathionine to cystine maybe predictive of the developmental toxicity/teratogenicity of a testcompound. Any one, two or all three of these ration may be utilized inthe determination of the developmental toxicity of a compound.

With the present invention, a change in the secretome elicited by testcompound exposure relative to untreated cultures produces a metabolicsignature that may be used for measuring cell viability. Changes incellular metabolism as measured in the spent medium following cellculture are a functional measure of cell health. The change in thesecretome elicited by exposure to a test agent relative to untreatedcultures produces a metabolic signature that can be used to infer thenumber of metabolically viable cells present within a cell culture. Oneor more of the secreted metabolites described herein can be utilized toinfer the number viable cells relative to the number of cells in areference culture “control group.” These metabolites could be utilizedto determine the number of viable cells within a cell culture without arequirement to destroy or impact the cells. These metabolites can beused as novel measure of viability that does not require disrupting thegrowing cells.

With the present invention, a change in the secretome elicited byexposure to a range of concentrations of a test compound relative tountreated cultures may be used to determine the concentration at which atest compound is teratogenic. The teratogenic potential of a compound isassociated with the level of exposure to the fetus. Therefore a compoundcould be considered both teratogenic and non-teratogenic depending onthe exposure level. For example, retinol (vitamin A), when taken at orbelow the Food and Drug Administration (FDA) maximum recommended dailyallowance (RDA; 8,000 IU), does not have an adverse effect on thedeveloping fetus. However, high doses of retinol (>25,000 IU/day) havebeen shown to cause malformations similar to those seen following 13-cisretinoic acid exposure in both experimental animals and humans(Teratology Society, 1987, “Teratology Society position paper:recommendations for vitamin A use during pregnancy,” Teratology;35:269-275).

In some aspects, the teratogenicity of a compound may be tested atconcentrations corresponding to their IC50 or EC50 dose levels, atconcentrations corresponding to their circulating dose, atconcentrations corresponding to in maternal circulation and/or atconcentrations corresponding to the test compound's human therapeuticC_(max). Such dosing recapitulates the exposure level to a developinghuman embryo in vivo and the toxic or teratogenic effect of the dosingcompound on human development.

In some aspects, the teratogenicity of a compound may be tested over arange of concentrations of the test compound. Such a range may include,for example, about 0.04 μM to about 300 μM, about 4 μM to about 30,000μM, and about 0.0001 μM to about 10 μM. Such a range may include, forexample, a serial dilution of, for example, five, six, seven, eight,nine, ten, or more dilutions. Such dilutions may be, for example,two-fold, three-fold, four-fold, five-fold, ten-fold, or more.

With the present invention, individual metabolites and/or ratios of foldchanges may be utilized in concordance with cell viability data for theprediction of developmental toxicity. The quickPredict method describedherein combines cell culture based evaluation of a nine-point dose curvewith a metabolic index to predict the dose at which a test agent mayexhibit developmental toxicity and cytotoxicity within a seven day timeframe. This assay workflow represent a significant five-fold increase inthroughput over traditional ‘omics’ based computational approaches. Inthe previously described devTox assay (see, for example,PCT/US2011/029471 and U.S. patent application Ser. No. 13/069,326(“Predicting Human Developmental Toxicity of Pharmaceuticals Using HumanStem-Like Cells and Metabolomics,” West et al., 2010, Toxicol ApplPharmacol; 247(1):18-27, and Kleinstreuer et al., 2011, Toxicol ApplPharmacol; 257(1):111-121), stem cells are dosed with a test compound intwo steps, (1) at multiple concentrations for cell viabilitymeasurements which are performed to determine the optimal dose levelsfor metabolomics studies that provide a maximum metabolic response witha minimum of cell death, and (2) then after the best concentration wasdetermined, a new batch of cells is then dosed with 3 concentrationsderived from the optimal concentration and IC₅₀, the media is collectedfor LC-MS analysis using both ESI positive and ESI negative ionizationpolarities. In the QuickPredict methods of the present invention, mediais collected from the first step 96-well plates containing the cellsdosed at multiple concentrations and is analyzed directly on the massspectrometer using a much shorter LC gradient (6.5 minutes versus 23minutes for the previous method), using only positive polarity ESI. Insome aspects, the QuickPredict method may utilize a Waters Acquity UPLCBEH Amide 2.1×50 1.7 uM column, rather than a longer Phenomenex LunaHILIC 100×3 mm 1.7 uM column. LC-MS data can be acquired for two 96 wellplates (corresponding to 2 test compounds) in 18 hours.

In some aspects, a fold change ratio of other than about 1 is indicativeof the teratogenicity of the test compound, for example, a fold changeratio of greater than about 1 (for example, including, but not limitedto, about 1.01, about 1.02, about 1.03, about 1.04, about 1.05, about1.06, about 1.07, about 1.08, about 1.09, about 1.1, about 1.11, about1.12, about 1.13, about 1.14, about 1.15, about 1.16, about 1.17, about1.18, about 1.19, about 1.2, about 1.21, about 1.22, about 1.23, about1.24, about 1.25, about 1.26, about 1.27, about 1.28, about 1.29, about1.3, about 1.31, about 1.32, about 1.33, about 1.34, about 1.35, about1.36, about 1.37, about 1.38, about 1.39, about 1.4, about 1.41, about1.42, about 1.43, about 1.44, about 1.45, about 1.46, about 1.47, about1.48, about 1.49, or about 1.5) and/or a fold change ratio of less thanabout 1 (for example, including, but not limited to, about 0.99, about0.98, about 0.97, about 0.96, about 0.95, about 0.94, about 0.93, about0.92, about 0.91, about 0.9, about 0.89, about 0.88, about 0.87, about0.86, about 0.85, about 0.84, about 0.83, about 0.82, about 0.81, about0.8, about 0.79, about 0.78, about 0.77, about 0.76, about 0.75, about0.74, about 0.73, about 0.72, about 0.71, about 0.7, about 0.69, about0.68, about 0.67, about 0.66, about 0.65, about 0.64, about 0.63, about0.62, about 0.61, about 0.6, about 0.59, about 0.58, about 0.57, about0.56, about 0.55, about 0.54, about 0.53, about 0.52, about 0.51, orabout 0.5).

For example, in some aspects, a fold change ratio of less than about 0.9and/or greater than about 1.1 is indicative of the teratogenicity of thetest compound and a fold change ratio of greater than about 0.9 and/orless than about 1.1 is indicative of the non-teratogenicity of the testcompound. In some aspects, a fold change ratio of less than or equal toabout 0.9 and/or greater than or equal to about 1.1 is indicative of theteratogenicity of the test compound and a fold change ratio of greaterthan about 0.9 and/or less than about 1.1 is indicative of thenon-teratogenicity of the test compound.

For example, in some aspects, a fold change ratio of less than about0.89 and/or greater than about 1.11 is indicative of the teratogenicityof the test compound and a fold change ratio of greater than about 0.89and/or less than about 1.11 is indicative of the non-teratogenicity ofthe test compound. In some aspects, a fold change ratio of less than orequal to about 0.89 and/or greater than or equal to about 1.11 isindicative of the teratogenicity of the test compound and a fold changeratio of greater than about 0.89 and/or less than about 1.1 isindicative of the non-teratogenicity of the test compound.

For example, in some aspects, a fold change ratio of less than about0.88 and/or greater than about 1.12 is indicative of the teratogenicityof the test compound and a fold change ratio of greater than about 0.88and/or less than about 1.12 is indicative of the non-teratogenicity ofthe test compound. In some aspects, a fold change ratio of less than orequal to about 0.88 and/or greater than or equal to about 1.12 isindicative of the teratogenicity of the test compound and a fold changeratio of greater than about 0.88 and/or less than about 1.12 isindicative of the non-teratogenicity of the test compound.

For example, in some aspects, a fold change ratio of less than about0.87 and/or greater than about 1.13 is indicative of the teratogenicityof the test compound and a fold change ratio of greater than about 0.87and/or less than about 1.13 is indicative of the non-teratogenicity ofthe test compound. In some aspects, a fold change ratio of less than orequal to about 0.87 and/or greater than or equal to about 1.13 isindicative of the teratogenicity of the test compound and a fold changeratio of greater than about 0.87 and/or less than about 1.13 isindicative of the non-teratogenicity of the test compound.

For example, in some aspects, a fold change ratio of less than about0.86 and/or greater than about 1.14 is indicative of the teratogenicityof the test compound and a fold change ratio of greater than about 0.86and/or less than about 1.14 is indicative of the non-teratogenicity ofthe test compound. In some aspects, a fold change ratio of less than orequal to about 0.86 and/or greater than or equal to about 1.14 isindicative of the teratogenicity of the test compound and a fold changeratio of greater than about 0.86 and/or less than about 1.14 isindicative of the non-teratogenicity of the test compound.

For example, in some aspects, a fold change ratio of less than about0.85 and/or greater than about 1.15 is indicative of the teratogenicityof the test compound and a fold change ratio of greater than about 0.85and/or less than about 1.15 is indicative of the non-teratogenicity ofthe test compound. In some aspects, a fold change ratio of less than orequal to about 0.85 and/or greater than or equal to about 1.15 isindicative of the teratogenicity of the test compound and a fold changeratio of greater than about 0.85 and/or less than about 1.15 isindicative of the non-teratogenicity of the test compound.

For example, in some aspects, a fold change ratio of less than about0.84 and/or greater than about 1.16 is indicative of the teratogenicityof the test compound and a fold change ratio of greater than about 0.84and/or less than about 1.16 is indicative of the non-teratogenicity ofthe test compound. In some aspects, a fold change ratio of less than orequal to about 0.84 and/or greater than or equal to about 1.16 isindicative of the teratogenicity of the test compound and a fold changeratio of greater than about 0.84 and/or less than about 1.16 isindicative of the non-teratogenicity of the test compound.

A determination of a metabolite, fragment, adduct, deduct or lossthereof, may be identified using a physical separation method. In someembodiments, a metabolite, fragment, adduct, deduct or loss thereof, maybe identified using a methodology other than a physical separationmethod. Such measurement methods may include, for example, colorimetricassays, enzymatic assays, or immunological assays. Immunological assaysmay include, for example, IF, RIA, ELISA and other immunoassays.Alternatively, certain biomarkers can be identified by, for example,gene expression analysis, including real-time PCR, RT-PCR, Northernanalysis, and in situ hybridization.

The term “physical separation method” as used herein refers to methodknown to those with skill in the art sufficient to produce a profile ofchanges and differences in small molecules produced in hSLCs, contactedwith a toxic, teratogenic or test chemical compound. In someembodiments, physical separation methods permit detection of cellularmetabolites including but not limited to sugars, organic acids, aminoacids, fatty acids, hormones, vitamins, and oligopeptides, as well asionic fragments thereof and low molecular weight compounds (preferablywith a molecular weight less than 3000 Daltons, and more particularlybetween 50 and 3000 Daltons). For example, mass spectrometry can beused. In particular embodiments, this analysis may be performed byliquid chromatography/electrospray ionization time of flight massspectrometry (LC/ESI-TOF-MS). However it will be understood thatmetabolites as set forth herein can be detected using alternativespectrometry methods or other methods known in the art, including, butnot limited to, any of those described herein.

For example, biomarkers are identified by methods includingLC/ESI-TOF-MS and/or QTOF-MS. Metabolomic biomarkers are identified bytheir unique molecular mass and consistency with which the marker isdetected in response to a particular toxic, teratogenic or test chemicalcompound; thus the actual identity of the underlying compound thatcorresponds to the biomarker is not required for the practice of thisinvention.

Biomarkers may be identified using, for example, Mass Spectrometry suchas MALDI/TOF (time-of-flight), SELDI/TOF, liquid chromatography-massspectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS), highperformance liquid chromatography-mass spectrometry (HPLC-MS), capillaryelectrophoresis-mass spectrometry, nuclear magnetic resonancespectrometry, tandem mass spectrometry (e.g., MS/MS, MS/MS/MS, ESI-MS/MSetc.), secondary ion mass spectrometry (SIMS), and/or ion mobilityspectrometry (e.g. GC-IMS, IMS-MS, LC-IMS, LC-IMS-MS etc.).

In some aspects, a gas phase ion spectrophotometer may be used. In otheraspects, laser-desorption/ionization mass spectrometry may be used toidentify biomarkers. For example, modern laser desorption/ionizationmass spectrometry (LDI-MS) may be practiced in two main variations;matrix assisted laser desorption/ionization (MALDI) mass spectrometryand surface-enhanced laser desorption/ionization (SELDI). In MALDI, theanalyte is mixed with a solution containing a matrix, and a drop of theliquid is placed on the surface of a substrate. The matrix solution thenco-crystallizes with the biomarkers. The substrate is inserted into themass spectrometer. Laser energy is directed to the substrate surfacewhere it desorbs and ionizes the proteins without significantlyfragmenting them. However, MALDI has limitations as an analytical tool.It does not provide means for fractionating the biological fluid, andthe matrix material can interfere with detection, especially for lowmolecular weight analytes. In SELDI, the substrate surface is modifiedso that it is an active participant in the desorption process. In onevariant, the surface is derivatized with adsorbent and/or capturereagents that selectively bind the biomarker of interest. In anothervariant, the surface is derivatized with energy absorbing molecules thatare not desorbed when struck with the laser. In another variant, thesurface is derivatized with molecules that bind the biomarker ofinterest and that contain a photolytic bond that is broken uponapplication of the laser. In each of these methods, the derivatizingagent generally is localized to a specific location on the substratesurface where the sample is applied. The two methods can be combined by,for example, using a SELDI affinity surface to capture an analyte (e.g.biomarker) and adding matrix-containing liquid to the captured analyteto provide the energy absorbing material.

Data from mass spectrometry may be represented as a mass chromatogram. A“mass chromatogram” is a representation of mass spectrometry data as achromatogram, where the x-axis represents time and the y-axis representssignal intensity. In one aspect the mass chromatogram may be a total ioncurrent (TIC) chromatogram. In another aspect, the mass chromatogram maybe a base peak chromatogram. In other aspects, the mass chromatogram maybe a selected ion monitoring (SIM) chromatogram. In yet another aspect,the mass chromatogram may be a selected reaction monitoring (SRM)chromatogram. In yet another aspect, the mass chromatogram may be anextracted ion chromatogram (EIC). In an EIC, a single feature ismonitored throughout the entire run. The total intensity or base peakintensity within a mass tolerance window around a particular analyte'smass-to-charge ratio is plotted at every point in the analysis. The sizeof the mass tolerance window typically depends on the mass accuracy andmass resolution of the instrument collecting the data. As used herein,the term “feature” refers to a single small metabolite, or a fragment ofa metabolite. In some embodiments, the term feature may also includenoise upon further investigation.

A person skilled in the art understands that any of the components of amass spectrometer, e.g., desorption source, mass analyzer, detect, etc.,and varied sample preparations can be combined with other suitablecomponents or preparations described herein, or to those known in theart. For example, a control sample may contain heavy atoms, e.g. ¹³C,thereby permitting the test sample to be mixed with the known controlsample in the same mass spectrometry run. Good stable isotopic labelingis included.

A laser desorption time-of-flight (TOF) mass spectrometer may be used.In laser desorption mass spectrometry, a substrate with a bound markeris introduced into an inlet system. The marker is desorbed and ionizedinto the gas phase by laser from the ionization source. The ionsgenerated are collected by an ion optic assembly, and then in atime-of-flight mass analyzer, ions are accelerated through a short highvoltage field and let drift into a high vacuum chamber. At the far endof the high vacuum chamber, the accelerated ions strike a sensitivedetector surface at a different time. Since the time-of-flight is afunction of the mass of the ions, the elapsed time between ion formationand ion detector impact can be used to identify the presence or absenceof molecules of specific mass to charge ratio. In one aspect, levels ofbiomarkers may be detected by MALDI-TOF mass spectrometry.

Methods of detecting biomarkers also include the use of surface plasmonresonance (SPR). The SPR biosensing technology may be combined withMALDI-TOF mass spectrometry for the desorption and identification ofbiomarkers.

A computer may be used for statistical analysis. Data for statisticalanalysis can be extracted from chromatograms (spectra of mass signals)using softwares for statistical methods known in the art. Statistics isthe science of making effective use of numerical data relating to groupsof individuals or experiments. Methods for statistical analysis arewell-known in the art.

For example, the Agilent MassProfiler or MassProfilerProfessionalsoftware may be used for statistical analysis. Or, the AgilentMassHunter software Qual software may be used for statistical analysis.Alternative statistical analysis methods can be used. Such otherstatistical methods include the Analysis of Variance (ANOVA) test,Chi-square test, Correlation test, Factor analysis test, Mann-Whitney Utest, Mean square weighted derivation (MSWD), Pearson product-momentcorrelation coefficient, Regression analysis, Spearman's rankcorrelation coefficient, Student's T test, Welch's T-test, Tukey's test,and Time series analysis.

In some aspects, signals from mass spectrometry can be transformed indifferent ways to improve the performance of the method. Eitherindividual signals or summaries of the distributions of signals (such asmean, median or variance) can be so transformed. Possibletransformations include taking the logarithm, taking some positive ornegative power, for example the square root or inverse, or taking thearcsin (Myers, Classical and Modern Regression with Applications, 2ndedition, Duxbury Press, 1990).

In some aspects, statistical classification algorithms can be used tocreate a classification model in order to predict teratogenicity andnon-teratogenicity of test compounds. Machine learning-based classifiershave been applied in various fields such as machine perception, medicaldiagnosis, bioinformatics, brain-machine interfaces, classifying DNAsequences, and object recognition in computer vision. Learning-basedclassifiers have proven to be highly efficient in solving somebiological problems.

As used herein, a “training set” is a set of data used in various areasof information science to discover potentially predictive relationships.Training sets are used in artificial intelligence, machine learning,genetic programming, intelligent systems, and statistics. In all thesefields, a training set has much the same role and is often used inconjunction with a test set.

As used herein, a “test set” is a set of data used in various areas ofinformation science to assess the strength and utility of a predictiverelationship. Test sets are used in artificial intelligence, machinelearning, genetic programming, intelligent systems, and statistics. Inall these fields, a test set has much the same role.

“Sensitivity” and “specificity” are statistical measures of theperformance of a binary classification test. Sensitivity measures theproportion of actual positives which are correctly identified as such(e.g. the percentage of sick people who are correctly identified ashaving the condition). Specificity measures the proportion of negativeswhich are correctly identified (e.g. the percentage of healthy peoplewho are correctly identified as not having the condition). These twomeasures are closely related to the concepts of type I and type IIerrors. A theoretical, optimal prediction can achieve 100% sensitivity(i.e. predict all people from the sick group as sick) and 100%specificity (i.e. not predict anyone from the healthy group as sick). Aspecificity of 100% means that the test recognizes all actualnegatives—for example, in a test for a certain disease, all disease freepeople will be recognized as disease free. A sensitivity of 100% meansthat the test recognizes all actual positives—for example, all sickpeople are recognized as being ill. Thus, in contrast to a highspecificity test, negative results in a high sensitivity test are usedto rule out the disease. A positive result in a high specificity testcan confirm the presence of disease. However, from a theoretical pointof view, a 100%-specific test standard can also be ascribed to a ‘bogus’test kit whereby the test simply always indicates negative. Thereforethe specificity alone does not tell us how well the test recognizespositive cases. A knowledge of sensitivity is also required. For anytest, there is usually a trade-off between the measures. For example, ina diagnostic assay in which one is testing for people who have a certaincondition, the assay may be set to overlook a certain percentage of sickpeople who are correctly identified as having the condition (lowspecificity), in order to reduce the risk of missing the percentage ofhealthy people who are correctly identified as not having the condition(high sensitivity). This trade-off can be represented graphically usinga receiver operating characteristic (ROC) curve.

The “accuracy” of a measurement system is the degree of closeness ofmeasurements of a quantity to its actual (true) value. The “precision”of a measurement system, also called reproducibility or repeatability,is the degree to which repeated measurements under unchanged conditionsshow the same results. Although the two words can be synonymous incolloquial use, they are deliberately contrasted in the context of thescientific method. A measurement system can be accurate but not precise,precise but not accurate, neither, or both. For example, if anexperiment contains a systematic error, then increasing the sample sizegenerally increases precision but does not improve accuracy. Eliminatingthe systematic error improves accuracy but does not change precision.

The term “predictability” (also called banality) is the degree to whicha correct prediction or forecast of a system's state can be made eitherqualitatively or quantitatively. Perfect predictability implies strictdeterminism, but lack of predictability does not necessarily imply lackof determinism. Limitations on predictability could be caused by factorssuch as a lack of information or excessive complexity.

In some aspects, a method of the present invention may predict theteratogenicity of a test compound with at least about 80% accuracy, atleast about 85% accuracy, at least about 90% accuracy, or at least about95% accuracy.

In some aspects, a method of the present invention may predict theteratogenicity of a test compound with at least about 80% sensitivity,at least about 85% sensitivity, at least about 90% sensitivity, or atleast about 95% sensitivity.

In some aspects, a method of the present invention may predict theteratogenicity of a test compound with at least about 80% specificity,at least about 85% specificity, at least about 90% specificity, or atleast about 95% specificity.

In some aspects, the methods described herein may utilize cystinedeterminations alone, or cystine in combinations with any of a varietyof other metabolites, including, but not limited to one or more of themetabolites described herein. For example, a determination of a foldchange in cystine alone can be used to classify teratogens, using athreshold of at least a 10% increase relative to the referencetreatment.

In some aspects, the methods described herein may utilize ornithinedeterminations alone, ornithine in combinations with any of a variety ofother metabolites, including, but not limited to one or more of themetabolites described herein. For example, a determination of a foldchange in ornithine alone can be used to classify teratogens, using athreshold of about a 20% increase and/or an 18.5% decrease relative tothe reference treatment.

In addition to determining altered ratios in the fold changes ofornithine to cystine, asymmetric dimethylarginine (ADMA) to cystine,and/or cystathionine to cystine, the accuracy of the methods describedherein may be improved by further determining the fold change in one ormore additional metabolites associated with hSLCs cultured in thepresence of the test compound in comparison with hSLCs cultured in theabsence of the test compound.

In some embodiments, a method may further include a determination of theratio of the fold change in arginine, or fragment, adduct, deduct orloss thereof, to the fold change in ADMA, or fragment, adduct, deduct orloss thereof. In some aspects, a ratio of less than at least about 0.9or greater than at least about 1.1 is indicative of the teratogenicityof the test compound and a ratio of greater than at least about 0.9 andless than at least about 1.1 is indicative of the non-teratogenicity ofthe test compound. See, for example, PCT/US2011/029471 and U.S. patentapplication Ser. No. 13/069,326 (“Predicting Human DevelopmentalToxicity of Pharmaceuticals Using Human Stem-Like Cells andMetabolomics”), West et al., 2010, Toxicol Appl Pharmacol; 247(1):18-27,and Kleinstreuer et al., 2011, Toxicol Appl Pharmacol; 257(1):111-121.

Additional metabolites may include, for example, one or more additionalmetabolites, two or more additional metabolites, three or moreadditional metabolites, four or more additional metabolites, five ormore additional metabolites, six or more additional metabolites, sevenor more additional metabolites, eight or more additional metabolites,nine or more additional metabolites, ten or more additional metabolites,eleven or more additional metabolites, twelve or more additionalmetabolites, thirteen or more additional metabolites, fourteen or moreadditional metabolites, or fifteen or more additional metabolites.

One or more additional metabolite may include a metabolite of ametabolic pathway selected from, for example, an alanine, aspartate andglutamate metabolic network; an arginine and proline metabolic network;an ascorbate and aldarate metabolic network; a citrate cycle; a cysteineand methionine metabolic network; a galactose metabolic network; aglutathione metabolic network; a glyoxylate and dicarboxylate metabolicnetwork; a nicotinate and nicotinamide metabolic network; a pantothenateand coenzyme A biosynthesis pathway; a pentose and glucoronateinterconversions pathway; a pentose phosphate pathway; a propanoatemetabolic network; a pyruvate metabolic network; and/or a vitamin B6metabolic network.

For example, one or additional metabolite may include a metabolite ofthe pantothenate and coenzyme A biosynthesis pathway, such as, forexample, pyruvate, L-valine, dimethylmalate, pantoate, patothenate,phosphorpatothenoyl-L-cyteine, 5,6-dihydrouracil, N-carbamoyl-β-alanine,and/or coenzyme A.

For example, one or additional metabolite may include a metabolite ofthe glutathione metabolic network, such as, for example, 5-oxoproline,L-glutamate, glycine, L-γ-glutamylcysteine, glycine, dehydroascorbate,glutathionyl spermine, and/or L-ornithine.

For example, one or additional metabolite may include a metabolite ofthe arginine and proline metabolic network, such as, for example,pyruvate, dimethlarginine, L-arginine, L-citrulline, glutamine,aspartate, L-argosuccinate, guanidino-acetate-phosphate, fumarate,sarcosine, 2-oxoarginine, pyruvate, 5-amino-pentanoate, linatine,pyrrole-2-carbosylate, putrescine, 6-oxo-1,4,5,6-tetrahydronicotinate,2,6-dihydroxynictinate, fumarate, and/or GABA.

For example, one or additional metabolite may include a metabolite ofthe nicotinate and nicotinamide metabolic network, such as, for example,6-oxo-1,4,5,6-tetrahydronicotinate, 2,6-dihydroxynictinate, and/orfumarate.

For example, additional metabolites may include one or more, two ormore, three or more, four or more, or five or more additionalmetabolites selected from cystine, N1-acetylspermidine, asymmetricdimethylarginine, cystathionine, 2′-deoxyuridine, GABA, malic acid,succinic acid, and aspartic acid.

For example, additional metabolites may include any one or more, any twoor more, any three or more, any four or more, any five or more, any sixor more, any seven or more, any eight or more, any nine or more, any tenor more, any eleven or more, any twelve or more, any thirteen or more,or any fourteen or more of the additional metabolites selected frommethylsulfonylacetonitrile; aspartic acid, N-acetylspermidine;dimethyl-L-arginine; L-cystathionine; GABA; fumaric acid; valine;succinic acid; aspartic acid; pantoic acid; the metabolite having m/z of215.1387, RT of 466, and ESI(+) polarity; the metabolite having m/z of234.8904, RT of 246, and ESI(+) polarity; the metabolite having m/z of251.0666, RT of 105, and ESI(+) polarity; and the metabolite having m/zof 403.0839, RT of 653, and ESI(+) polarity. In some aspects, all foldchanges in fifteen metabolites is determined. See, Table 11 ofPCT/US2011/029471 and U.S. patent application Ser. No. 13/069,326(“Predicting Human Developmental Toxicity of Pharmaceuticals Using HumanStem-Like Cells and Metabolomics”), each of which is hereby incorporatedby reference in its entirety.

The hSLC and metabolomics based methods of the present invention offer asignificant advantage over other studies that use mouse or zebrafish-based models to determine toxicity and teratogenicity of chemicalcompounds.

The methods of the present invention may be used for classifying a testcompound as a teratogen or a non-teratogen, for predicting theteratogenicity of a test compound, and/or for validating a test compoundas a teratogen. The methods of the present invention may also serve as ahigh throughput screening tool in preclinical phases of drug discovery.In addition, this approach can be used to detect detrimental effects ofenvironmental (heavy metals, industrial waste products) and nutritionalchemicals (such as alcohol) on human development. Further, the methodsof this invention can assist pharmaceutical, biotechnology andenvironmental agencies on decision-making towards development ofcompounds and critical doses for human exposure. The integration ofchemical biology to embryonic stem cell technology also offers uniqueopportunities to strengthen understanding of human development anddisease. Metabolomics of cells differentiated from hSLCs should servesimilar roles and be useful for elucidating mechanisms of toxicity anddisease with greater sensitivity for particular cell or tissue types,and in a human-specific manner.

Biomarker portfolios produced using the hSLC-dependent methods of thisinvention may also be used in high throughput screening methods forpreclinical assessment of drug candidates and lead compounds in drugdiscovery. This aspect of the inventive methods produces minimal impacton industry resources in comparison to current developmental toxicologymodels, since implementation of this technology does not requireexperimental animals. The resulting positive impact on productivityenables research teams in the pharmaceutical industry to select andadvance compounds into exploratory development with greater confidenceand decreased risk of encountering adverse developmental effects.

The present invention includes a kit for identifying and/or measuringone or more metabolites. In some aspects, the kit may be for thedetermination of a metabolite by a physical separation method. In someaspects, the kit may be for the determination of a metabolite by amethodology other than a physical separation method, such as forexample, a colorimetric, enzymatic, immunological methodology. In someaspects an assay kit may also include one or more appropriate negativecontrols and/or positive controls. Kits of the present invention mayinclude other reagents such as buffers and solutions needed to practicethe invention are also included. Optionally associated with suchcontainer(s) can be a notice or printed instructions. As used herein,the phrase “packaging material” refers to one or more physicalstructures used to house the contents of the kit. The packaging materialis constructed by well known methods, preferably to provide a sterile,contaminant-free environment. As used herein, the term “package” refersto a solid matrix or material such as glass, plastic, paper, foil, andthe like, capable of holding within fixed limits a polypeptide. Kits ofthe present invention may also include instructions for use.Instructions for use typically include a tangible expression describingthe reagent concentration or at least one assay method parameter, suchas the relative amounts of reagent and sample to be admixed, maintenancetime periods for reagent/sample admixtures, temperature, bufferconditions, and the like.

In some aspects, a kit may be a packaged combination comprising thebasic elements of a first container comprising, in solid form, aspecific set of one or more purified metabolites, as described herein,and a second container comprising a physiologically suitable buffer forresuspending the specific subset of purified metabolites.

The present invention is illustrated by the following examples. It is tobe understood that the particular examples, materials, amounts, andprocedures are to be interpreted broadly in accordance with the scopeand spirit of the invention as set forth herein.

EXAMPLES Example 1 Establishment and Assessment of a New Human EmbryonicStem Cell-Based Biomarker Assay for Developmental Toxicity Screening

With this example a metabolic biomarker-based in vitro assay utilizinghuman embryonic stem (hES) cells was developed to identify theconcentration of test compounds that perturbs cellular metabolism in amanner indicative of teratogenicity. This assay is designed to aid theearly discovery-phase detection of potential human developmentaltoxicants. In this study, metabolomic data from hES cell culture mediawas used to assess potential biomarkers for development of a rapid invitro teratogenicity assay. hES cells were treated with pharmaceuticalsof known human teratogenicity at a concentration equivalent to theirpublished human peak therapeutic plasma concentration. Two metabolitebiomarkers (ornithine and cystine) were identified as indicators ofdevelopmental toxicity. A targeted exposure-based biomarker assay usingthese metabolites, along with a cytotoxicity endpoint, was thendeveloped using a 9-point dose response curve. The predictivity of thenew assay was evaluated using a separate set of test compounds. Toillustrate how the assay could be applied to compounds of unknownpotential for developmental toxicity, an additional 10 compounds wereevaluated that do not have data on human exposure during pregnancy, buthave shown positive results in animal developmental toxicity studies.The new assay identified the potential developmental toxicants in thetest set with 77% accuracy (57% sensitivity, 100% specificity). Theassay had a high concordance (≧75%) with existing in vivo models,demonstrating that the new assay can predict the developmental toxicitypotential of new compounds as part of discovery phase testing andprovide a signal as to the likely outcome of required in vivo tests.

This example describes the development of a rapid, reproducible,biomarker-based screen for developmental toxicity testing designed toidentify the exposure level at which a test compound perturbs metabolismin a manner predictive of developmental toxicity. Perturbation of twometabolites, ornithine and cystine, in response to the test compound wasassessed across nine independent experimental replications to ensurerepeatability across experiments and liquid chromatography highresolution mass spectrometry (LC-HRMS) systems. Using theornithine/cystine ratio (o/c ratio), we developed a rapid, targetedassay that measured changes in metabolism and cellular viability acrossa 9-point dose response curve to determine the exposure level at which atest compound perturbs metabolism in a manner associated withdevelopmental toxicity potential. To assess the predictivity of theassay for known human teratogens in the training and test sets ofcompounds, the exposure level where a compound was predicted to havedevelopmental toxicity potential was scored against the compound's humanpeak plasma in vivo concentration (C_(max)) following therapeutic doses.The C_(max) value in this case is used as a benchmark exposure level toaid in interpreting the performance of the assay as it is the highestconcentration a human would normally be exposed to under therapeuticcircumstances and we would expect to detect developmental toxicity atthis exposure level.

However, application of the assay in the discovery stage of a compound'sdevelopment would not require this C_(max) information, and a testcompound's teratogenic potential is based on the exposure level at whicha test compound perturbs metabolism in a manner indicative ofteratogenicity. The design and sensitivity of the assay allows foridentification of teratogenic potential at non-cytotoxic levels of thetest compound, by negating the confounding effects of changes inmetabolite abundance due strictly to cytotoxicity. The ability toidentify developmental toxicity in the absence of cytotoxicity at avariety of exposure levels is a key strength of the assay anddistinguishes it from existing in vitro assays.

Useful Terms and Definitions

Teratogenicity Threshold. A threshold of metabolic perturbation that isassociated with the potential for teratogenesis. The threshold wasempirically determined to be 0.88 for the targeted biomarker assay usingthe training set results. This threshold was applied to all test set andunknown compounds evaluated using the assay.

Ornithine/Cystine Ratio (O/C Ratio). The fold change of ornithine (Orn)for treatment x divided by the fold change of cystine (Cyss) fortreatment x.

${O\text{/}C\mspace{14mu} {Ratio}} = \frac{\left( {{Orn}_{x}\text{/}{Orn}_{DMSO}} \right)}{\left( {{Cyss}_{x}\text{/}{Cyss}_{DMSO}} \right)}$

Teratogenicity Potential. Interpolated exposure level (concentration) ofa test compound where the dose response curve for the o/c ratio or cellviability crosses the teratogenicity threshold. Exposure levels greaterthan this concentration are associated with teratogenicity.

Accuracy. Number of correct predictions divided by the number testcompounds evaluated.

Sensitivity. Detection of teratogens, True Positives/(FalseNegatives+True Positives).

Specificity. Detection of non-teratogens, True Negatives/(TrueNegatives+False Positives).

Training Set. Set of compounds that have well established humandevelopmental toxicity information used to identify biomarkers ofdevelopmental toxicity. This set of compounds was tested in both phasesof the study and used to set the teratogenicity threshold.

Test Set. Set of compounds with well-established human developmentaltoxicity information that were not used to identify the biomarkers, butused to evaluate the predictivity of the biomarkers of developmentaltoxicity. This set of compounds was used to evaluate the performance ofthe targeted biomarker assay and the teratogenicity threshold set usingthe training set.

Application Set. Set of compounds with poorly defined humandevelopmental toxicity information used to demonstrate application ofthe assay. These compounds are not classified as a teratogen ornon-teratogen based on their C_(max) since human teratogenicity isunknown at this concentration.

Materials and Methods

Development and evaluation of the targeted biomarker-based assay wasconducted in two phases. In the first phase (Phase 1), the predictivepotential of two previously identified predictive biomarkers (ornithineand cystine, Kleinstreuer et al., 2011, Toxicol Appl Pharmacol;257:111-121) was characterized across nine independent experimentalreplications (experimental blocks) of the training set using untargetedmetabolomic methods. In the second phase (Phase 2), the predictivebiomarkers were used to develop a rapid turnaround, targeted,exposure-based assay for compound prioritization based on teratogenicitypotential. The predictivity of the new assay was evaluated using theoriginal training set as well as an independent test set of compounds.

Test Chemical Selection and Classification. A total of 46 compounds wereused to evaluate the ability of ornithine, cystine and the o/c ratio topredict developmental toxicity in two experimental phases. These 46compounds were divided into three groups, named the training, test, andapplication sets. The training set was a set of compounds that have wellestablished human developmental toxicity information used to identifybiomarkers of developmental toxicity. The test set was a set ofcompounds with well-established human developmental toxicity informationthat were not used to identify the biomarkers, but used to evaluate thepredictivity of the biomarkers of developmental toxicity. Theapplication set was a set of compounds with poorly defined humandevelopmental toxicity information used to demonstrate application ofthe assay. These compounds are not classified as a teratogen ornon-teratogen based on their C_(max) since human teratogenicity isunknown at this concentration.

The training set consisted of 23 well characterized pharmaceuticalcompounds (11 known human non-teratogens and 12 known human teratogens,Table 2) and was previously used to build a computational model andidentify biomarkers predictive of teratogenicity (Kleinstreuer et al.,2011, Toxicol Appl Pharmacol; 257:111-121). This training set wasutilized in both experimental phases. To assess the predictive capacityof the targeted biomarker assay developed in these studies, anadditional test set of 13 well characterized pharmaceutical compounds (6known human non-teratogens and 7 known human teratogens, Table 3) wasused in the second experimental phase to evaluate the predictivity ofthe new assay. The final set of compounds (the application set, Table 4)consists of 10 compounds that do not have conclusive developmentaltoxicity data available on exposure during human pregnancy, but do haveanimal data available on developmental toxicity potential. A two-classsystem of compound classification (teratogen and non-teratogen) wasapplied for assay development, focusing the teratogenicityclassification strictly on observed human risk associated with eachchemical. Compounds were purchased from Sigma-Aldrich (St. Louis, Mo.),except for amprenavir, bosentan, entacapone (Toronto Research Chemicals,Toronto, Ontario, Canada), lapatinib (Chemie Tek, Indianapolis, Ind.),cidovofir and ramelteon (Selleck Chemicals, Houston, Tex.).

TABLE 1 Description of the Training Set Compounds. FDA Preclinical invivo and Pregnancy known human Compound Pharmacology/Chemical ClassCategory^(a) developmental effects^(b) Human Non-teratogens AscorbicAcid Vitamin A None Caffeine Central Nervous System C Low Doses: None;High Stimulant Doses: Limb, craniofacial, embryo toxicity^(c)Diphenhydramine Antihistamine/H1 histamine B None receptor antagonistDoxylamine Antihistamine/H1 histamine B None receptor antagonist FolicAcid Vitamin A None Isoniazid Antibacterial/Antitubercular C NoneLevothyroxine Synthetic hormone A None Penicillin G Antibiotic B NoneRetinol Vitamin C Low Doses: None; High Doses: Craniofacial, centralnervous system, cardiovascular, skeletal Saccharin Artificial SweetenerA None Thiamine Vitamin A None Human Teratogens 13-cis Retinoic RAR/RXRligand X Craniofacial, limb, central Acid nervous system,cardiovascular, skeletal 5-Fluorouracil Antineoplastic/Antimetabolite DCraniofacial, central nervous system, skeletal All-trans RetinoicRAR/RXR ligand D Craniofacial, limb, central Acid nervous system,cardiovascular, skeletal, embryo toxicity^(c) BusulfanAntineoplastic/Alkylating D Craniofacial, limb, embryo toxicity^(c)Carbamazepine Anticonvulsant D Craniofacial, central nervous system,cardiovascular Cytosine Antineoplastic/Antimetabolite D Limb ArabinosideDiphenylhydantoin Anticonvulsant D Craniofacial, limb, cardiovascular,neurobehavioral Hydroxyurea Antineoplastic/Enzyme Inhibitor D Centralnervous system, craniofacial, limb, cardiovascular, embryo toxicity^(c)Methotrexate Antineoplastic/Dihydrofolate X Craniofacial, limb,skeletal, acid reductase inhibitor central nervous system, embryotoxicity^(c) Thalidomide Immunomodulant X Craniofacial, cardiovascular,limb, embryo toxicity^(c) Valproic Acid Anticonvulsant/GABA inhibitor DCentral nervous system, craniofacial, cardiovascular, skeletal,neurobehavioral, embryo toxicity^(c) Warfarin Anticoagulant X Centralnervous system, craniofacial, skeletal, embryo toxicity^(c) ^(a)FDAclassification requirements described in Shuren (2008, Federal Register;73: 30831-30868). ^(b)The preclinical in vivo and known humandevelopmental effects were summarized from the Teratogen InformationSystem (TERIS, see the worldwide web atdepts.washington.edu/terisweb/teris/) and Briggs et al. (2011, “Drugs inpregnancy and lactation,” 9th ed. Philadelphia: Lippincott Williams &Wilkins). ^(c)Embryo toxicity in addition to teratogenic effects (e.g.,growth retardation, embryo lethality).

TABLE 2 Description of the Test Set Compounds. FDA Preclinical in vivoand Pregnancy known human Compound Pharmacology/Chemical ClassCategory^(a) developmental effects^(b) Human Non-teratogensAcetaminophen Analgesic B None Acycloguanosine Antiviral B NoneAmoxicillin Antibiotic B None Loratadine Antihistamine/H1 histamine BNone receptor antagonist Metoclopramide Antiemetic B None SitagliptinHypoglycemic B Low doses: None; High doses: Skeletal Human TeratogensAminopterin Antineoplastic/Dihydrofolate acid X Craniofacial, limb,skeletal, reductase inhibitor central nervous system BosentanAntihypertensive X Craniofacial, cardiovascular D-Penicillamine ChelatorD Skeletal Everolimus Immunosuppressive D Skeletal, embryo toxicity^(c)Lapatinib Antineoplastic/Protein Kinase D Skeletal, embryo toxicity^(c)Inhibitors Lovastatin Anticholesteremic X Skeletal, embryo toxicity^(c)ThioTEPA Antineoplastic/Alkylating D Skeletal, embryo toxicity^(c)^(a)FDA classification requirements described in Shuren (2008, FederalRegister; 73: 30831-30868). ^(b)The preclinical in vivo and known humandevelopmental effects were summarized from the Teratogen InformationSystem (TERIS, see the worldwide web atdepts.washington.edu/terisweb/teris/) and Briggs et al. (2011, “Drugs inpregnancy and lactation,” 9th ed. Philadelphia: Lippincott Williams &Wilkins). ^(c)Embryo toxicity in addition to teratogenic effects (e.g.,growth retardation, embryo lethality).

TABLE 3 Description of the Application Set Compounds. FDAPharmacology/Chemical Pregnancy Preclinical in vivo Compound ClassCategory^(a) developmental effects^(b) 6-Aminonicotinamide NicotinicAcid Antagonist NA Craniofacial Abacavir Anti-HIV C Skeletal, embryotoxicity^(c) Adefovir dipivoxil Antiviral C None Amprenavir Anti-HIV CSkeletal, embryo toxicity^(c) Artesunate Antimalarial NA Cardiovascular,skeletal, embryo toxicity^(c,d) Cidofovir Antiviral C None EntacaponeAntiparkinson C Eye defects Fluoxetine Serotonin reuptake inhibitor CEmbryo toxicity^(c) Ramelteon Sedative/Hypnotics C None RosiglitazoneHypoglycemic C Embryo toxicity^(c) ^(a)FDA classification requirementsdescribed in Shuren (2008, Federal Register; 73: 30831-30868). ^(b)Thepreclinical in vivo and known human developmental effects weresummarized from the Teratogen Information System (TERIS, see theworldwide web at depts.washington.edu/terisweb/teris/) and Briggs et al.(2011, “Drugs in pregnancy and lactation,” 9th ed. Philadelphia:Lippincott Williams & Wilkins). ^(c)Embryo toxicity in addition toteratogenic effects (e.g., growth retardation, embryo lethality).^(d)Clark, 2009, Reprod Toxicol; 28: 285-296.

Undifferentiated hES Cell Line Maintenance (Phases 1 and 2). WA09 hEScells were obtained from the WiCell Research Institute (Madison, Wis.)and were maintained in feeder free conditions using mTeSR1 media(StemCell Technologies, Inc., Vancouver, BC, Canada) on hESC-qualifiedMatrigel (BD Biosciences, San Jose, Calif.) coated 6-well plates. Tomaintain the undifferentiated stem cell population, differentiatedcolonies were removed daily through aspiration and media was replaced.Additionally, the hES cells were only used in experiments up to passage40 and were karyotyped approximately every 10 passages to minimize andmonitor the potential for genetic instability. hES cells were passagedat 90-95% confluency (approximately every 7 days) using Versene (LifeTechnologies, Grand Island, N.Y.). Cell cultures were maintained at 37°C. under 5% CO₂.

96-well hES Cell Plating (Phases 1 and 2). All experimental treatmentswere carried out in 96-well plates. To minimize plating variability andincrease reproducibility, hES cells were plated as a single cellsuspension and maintained in an undifferentiated state during compoundexposure. Prior to plating in the 96-well plates, hES cells were removedfrom a E-well plate using TrypLE (Life Technologies). The cells werewashed with DMEM/F12 (Life Technologies) and resuspended in mTeSR1containing 10 μM Y27632 Rho-associated kinase (ROCK) inhibitor (MerckKGaA/Calbiochem, Darmstadt, Germany). The ROCK inhibitor is added to theplating media to increase plating efficiency by decreasingdissociation-induced apoptosis. The inner 60 wells of hESC-qualifiedMatrigel coated 96-well plates were seeded at a density of 100,000 cellsper well. The outer wells of the plate contained an equal volume mediato minimize differences in humidity across the plate. Compound exposurebegan 24 hours after plating.

Phase I hES Cell Compound Exposure. hES cells were treated with a testcompound at a single concentration equivalent to the compound'spublished therapeutic C_(max). The therapeutic C_(max) was used becauseit is considered to be a physiologically relevant exposure level and hasbeen correlated with the developmental effect of the compound (NationalResearch Council, 2000, “Scientific frontiers in developmentaltoxicology and risk assessment,” Washington, D.C.: The NationalAcademies Press). For six compounds (5-fluorouracil, aminopterin,busulfan, cytosine arabinoside, hydroxyurea and methotrexate) anexperimentally determined IC₃₀ was used in place of the C_(max) valuedue to greater than 30% cytotoxicity at the C_(max) exposure level. Thiswas done to ensure that enough cells were present at the time of samplecollection to provide a signal for LC-HRMS analysis. For test compoundexposure, all compound stock solutions, with the exception of valproicacid, were made with DMSO (Sigma-Aldrich). Valproic acid was insolublein DMSO at the concentrations used in this study, so it was diluted inmTeSR1 containing 0.1% DMSO. Each 96-well plate included media controlswith and without test compound, 0.1% DMSO solvent control cells andcells exposed to a single concentration of eight different testcompounds (FIG. 1A). Media controls were included on each plate toassess the impact of test compound on the sample matrix. hES cells wereexposed to the test compound for 72 hours, with media and test compoundreplacement every 24 hours. Cells were monitored throughout thetreatment period to ensure that no differentiation was occurring. After72 hours of treatment, the spent media from the final 24-hour treatmentperiod was collected and added to acetonitrile (Sigma-Aldrich, finalacetonitrile concentration 40%), to halt metabolic processes andprecipitate proteins from solution. Individual wells from each 96-wellplate were collected and analyzed as separate samples. These sampleswere then stored at −80° C. until prepared for LC-HRMS analysis. Cellviability was assessed using the CellTiter-Fluor Cell Viability Assay asper the manufacturer's instructions (Promega, Madison, Wis.). Qualitycontrol parameters were set such that if the coefficient of variation(CV) for the viability relative fluorescent units (RFU) of the 6cellular samples in a treatment exceeded 10% and no outliers wereidentified using the Grubb's test (see the worldwide web atgraphpad.com/quickcalcs/Grubbs1.cfm), analysis was halted for thatcompound and the cell culture experiment was repeated. If outliers werepresent, the outlier sample was removed from analysis. If the CV for theDMSO control cell samples on a plate were outside of the quality controlparameters, the entire plate was repeated. hES cell exposure to each ofthe 23 compounds was replicated a total of nine times.

Phase 2 hES Cell Compound Exposure. The predictivity of the targetedbiomarker assay was evaluated in the original training set as well as anindependent test set (Tables 2 and 3). The assay was additionallyapplied to the application set of compounds (Table 4) to demonstrateutility when human teratogenicity is unknown. The standard compoundexposure levels used for most compounds were nine, 3-fold dilutionsranging from 0.04 μM-300 μM (FIG. 1B). The exposure range for valproicacid was increased to 4 μM-30,000 μM because its therapeutic C_(max) wasoutside the standard exposure range. Compounds that were cytotoxic atconcentrations below 1 μM were repeated at lower exposure levels (0.001μM-10 μM). A stock solution of each test compound was prepared in 100%DMSO at a concentration of 1000 times the highest exposure level, withthe exception of ascorbic acid, folic acid, and valproic acid. Thesethree compounds were completely insoluble in DMSO and stocks wereprepared in mTeSR1 containing 0.1% DMSO. The stock solution was diluted1:1000 in mTeSR1 media and subsequent dilutions were performed in mTeSR1containing 0.1% DMSO such that the final concentration of DMSO was 0.1%in all treatments. hES cells were treated for 72 hours and spent mediafrom the last 24-hour treatment period was collected and added toacetonitrile containing ¹³C₆ labeled arginine (Cambridge IsotopeLaboratories, Andover, Md.) as described under Phase 1. Spent mediasamples were stored at −80° C. until prepared for LC-HRMS analysis. Cellviability was assessed using the CellTiter-Fluor Cell Viability Assay. Aquality control step was included with criteria that the CV of themeasured viability RFU of the DMSO control cells could not exceed 10%for a plate to undergo LC-HRMS analysis. A dose response curve was fitto the reference treatment (0.1% DMSO treated control cells) normalizeddata (Viability RFU_(Trt X)/Viability RFU_(DMSO)) using a four-parameterlog-logistic model with the R package “drc” (Ritz and Streibig, 2005, JStatistical Software; 12:1-22).

Sample Preparation (Phases 1 and 2). High molecular weight constituents(>10 KDa) of the spent media samples were removed using a MilliporeMultiscreen Ultracel-10 filter plate (EMD Millipore, Billerica, Mass.).Prior to sample filtration, the filter plate was washed with 0.1% NaOHto remove a known contaminant polymer. The plate was then rinsed twicewith HPLC-grade water to remove residual polymers and NaOH. Spent mediasamples were added to the washed filter plate. In Phase 1, samples werespiked with ¹³C₆ labeled arginine. Samples were centrifuged at 2,000×gat 4° C. for 200 minutes. The filtrate was collected and concentratedovernight in a Savant High Capacity Speedvac Plus Concentrator. Theconcentrated sample was resolubilized in a 1:1 0.1% formic acid inwater: 0.1% formic acid in acetonitrile mixture containing ¹³C₅ labeledglutamic acid (Cambridge Isotope Laboratories). The ¹³C labeledcompounds were used as internal standards to track preparatoryefficiency and track LC-HRMS performance.

Phase 1 Mass Spectrometry. LC-HRMS data was acquired for nine biologicalreplications on three separate LC-HRMS systems with three replicationsevaluated on each system. Each system consisted of an Agilent 1290Infinity LC system interfaced either with an Agilent G6520A QTOF highresolution mass spectrometer (QTOF HRMS), an Agilent G6530A QTOF HRMS,or an Agilent G6224A TOF HRMS system (Agilent Technologies, Santa Clara,Calif.). To facilitate separation of biological small molecules with awide range of structures and to allow increased retention of hydrophilicspecies, Hydrophilic Interaction Liquid Chromatography (HILIC) wasutilized. A Luna HILIC column (Phenomenex, Torrance, Calif.) withdimensions 3×100 mm and 3 μm particle size was used and maintained at30° C. Sample (2 μL) was injected and the data acquisition time was 23minutes (min) at a flow rate of 0.5 ml/min, using a 17 min solventgradient with 0.1% formic acid in water (Solvent A) and 0.1% formic acidin acetonitrile (Solvent B). Electrospray ionization was employed usinga dual ESI source. The scan range of the instrument was 70-1600 Da. Dataacquisition was performed with MassHunter Acquisition software (versionB 04.00, Agilent Technologies) using high-resolution exact massconditions and each set of samples was run first under ESI positivepolarity then under ESI negative polarity conditions.

Phase 2 Mass Spectrometry. Data was acquired to assess the performanceof the targeted biomarker assay using two instrument platforms. Ultrahigh performance liquid chromatography (UPLC)-HRMS data acquisition foreach compound was performed using one of two systems. System 1 consistedof an Agilent 1290 Infinity LC system interfaced with an Agilent G6520AQTOF HRMS. System 2 used the same model LC system interfaced with anAgilent G6224A TOF HRMS. A Waters Acquity UPLC BEH Amide 2.1×50 mm 1.7μm particle size column (Waters, Milford, Mass.) maintained at 40° C.was applied for separation of metabolites. A solvent gradient with 0.1%formic acid in water (Solvent A) and 0.1% formic acid in acetonitrile(Solvent B) at a flow rate of 1.0 ml/min was used and 2 μL of sample wasinjected. Electrospray ionization was employed using a dual ESI sourceoperated in positive ionization mode only. The mass range of theinstrument was set to 60-1600 Da and data was acquired over 6.5 minusing MassHunter Acquisition software (version B 04.00). Identificationof cystine and ornithine metabolites in samples was previously confirmedby comparison of their collision-induced dissociation mass spectra toreference standards (Sigma-Aldrich).

Peak Detection (Phases 1 and 2). Agilent raw data files were convertedto the open source mzData file format using MassHunter QualitativeAnalysis software version 5.0 (Agilent Technologies). During theconversion process, deisotoping (+1 charge state only) was performed onthe centroid data and peaks with an absolute height less than 200 wereexcluded from analysis. Peak picking and feature creation were performedusing the R package “xcms” (Smith et al., 2006, Anal Chem; 78:779-787).Mass features (peaks) were detected using the centwave algorithm.Deviations in retention times were corrected using the obiwarp algorithmthat is based on a non-linear clustering approach to align the data fromthe LC-MS samples. Mass feature bins or groups were generated using adensity based grouping algorithm. After the data had been grouped intomass features, missing features were integrated based on retention timeand mass range of a feature bin using the iterative peak filling.Feature intensity is based on the Mexican hat integration values of thefeature extracted ion chromatograms.

Ornithine/Cystine Ratio Calculation. In both phases of the study, every96-well plate of samples contained a reference treatment (0.1% DMSO) toallow compensation for the differences in LC-MS instrument response overtime. Relative fold changes were calculated for each metabolite bydividing the integrated area of each sample within a treatment level bythe median integrated area of the reference treatment (DMSO) samples toproduce a normalized value for both metabolites in each sample within aplate of cell culture samples. The o/c ratio was calculated for eachsample in a treatment by dividing the reference normalized value ofornithine by the reference normalized value of cystine. In Phase 2, afour-parameter log-logistic model of dose response was fit using themean o/c ratio value of each concentration using the R package “drc”(Ritz and Streibig, 2005, J Statistical Software; 12:1-22).

Teratogenicity Threshold Selection (Phases 1 and 2). Classification ofteratogenicity was based on the premise that a threshold of metabolicperturbation could be identified for individual metabolites that isassociated with developmental toxicity. This threshold of metabolicchange is called the teratogenicity threshold and is a measure of themagnitude of metabolic perturbation required to differentiate teratogensfrom non-teratogens. The teratogenicity threshold was empiricallygenerated for ornithine, cystine, and the o/c ratio by iteration througha range from 10% to 25% change, to identify a one-sided or two-sidedasymmetrical threshold that was able to classify the training set withthe greatest accuracy and highest sensitivity. In the case of a tie inclassification accuracy and sensitivity between one-sided and two-sidedthresholds, one-sided thresholds were given priority to favorsimplicity. A teratogenicity threshold was determined for each phase ofthe study, since the assays performed in Phase 1 used only a singleconcentration of each compound and the targeted biomarker assaydeveloped in Phase 2 utilized an exposure based approach. Theteratogenicity threshold was determined in Phase 2 using only theresults from the training set. This threshold was then applied to theresults from the test and application sets.

Phase 1 Prediction of Developmental Toxicity Potential. A test compoundwas classified as a developmental toxicant if the mean of the change inthe abundance in the treated sample compared to the reference treatment(DMSO) across the nine experimental replications for either metaboliteor the o/c ratio exceeded its respective teratogenicity threshold at theconcentration tested. The predictive accuracy (correct prediction),sensitivity (true positive rate), and specificity (true negative rate)were based on scoring the predicted result (teratogen or non-teratogen)against the known human teratogenicity of the compound.

Phase 2 Prediction of Developmental Toxicity Potential. For testcompounds with unknown developmental toxicity potential, the targetedbiomarker assay is utilized to identify the exposure level where a testcompound perturbs metabolism in a manner indicative of teratogenicityand does not require any pharmacokinetic information (e.g., C_(max)).FIG. 2 illustrates how the assay is applied in this situation. A testcompound is considered to be teratogenic at the exposure level where theo/c ratio exceeds the teratogenicity threshold (red box, FIG. 2). Theinterpolated concentration from the four-parameter log-logistic model ofthe o/c ratio or cell viability at the teratogenicity threshold isconsidered to be the teratogenicity potential exposure level of a testcompound (FIG. 2). Exposure levels greater than the teratogenicitypotential concentrations are predicted to have developmental toxicitypotential.

In order to assess the predictivity of the assay in the training andtest sets, the teratogenicity potential concentrations determined fromthe o/c ratio and cell viability were used to classify theteratogenicity of the test compound relative to the human therapeuticC_(max) concentrations. This approach was not applied to the applicationset since the developmental toxicity potential of these compounds inhumans is unknown. The logic of scoring a test compound as a teratogenor non-teratogen using the human therapeutic C_(max) is based on theparadigm that exposure is a critical factor in teratogenesis, and that aknown human teratogen would likely perturb cellular metabolism at orbelow the highest exposure that is likely to occur at the therapeuticcirculating levels. If perturbation of the o/c ratio was exhibited atconcentrations greater than the compound's C_(max) concentration (FIG.3A), it was scored as a non-teratogen because perturbation was observedoutside of a range likely to be encountered during routine therapy. If acompound exhibited teratogenicity potential at a concentration that wasat or below its therapeutic C_(max) it was classified as a teratogen(FIG. 3B), since a metabolic perturbation indicative of teratogenesiswas exhibited within the therapeutic concentration range. Theteratogenicity potential concentration from cell viability was used topredict the teratogenicity of a compound using the same paradigm. Thepredictive accuracy, sensitivity, and specificity of the assay werecalculated by comparing the predicted result to the known humanteratogenicity of a compound.

Comparison of the Targeted Biomarker Assay to Other DevelopmentalToxicity Tests. A literature review compared the developmental toxicityprediction of the in vivo rodent and rabbit models and three in vitroscreens (the European Centre for the Validation of Alternative Methods(ECVAM)-evaluated mouse embryonic stem cell test (mEST), the zebrafishembryotoxicity test (ZET), and the post-implantation rat whole embryoculture (WEC) test) for the compounds tested in the targeted biomarkerassay. The predictions made in these assays using each original author'sclassification methods were used for comparison and the data was notreinterpreted. The other in vitro systems employ a three classclassification system (non-, weak/moderate, and strong teratogens;Brown, 2002, Altern Lab Anim; 30:177-198), compared to the two classsystem used in this study. Thus, in order to compare the results fromthe targeted biomarker assay to other models, the predicted results fromthese assays needed to be modified to a two class system. Compounds thatwere predicted to be either weak/moderate or strong teratogens were bothlabeled as a predicted teratogen. The accuracy, sensitivity andspecificity were calculated for each assay by scoring the predictedresult against the known human teratogenicity. These values wereadditionally calculated for the targeted biomarker assay for thespecific set of compounds that had been tested in the other modelsystem. Concordance between the targeted biomarker assay and the otherabove-mentioned models was evaluated by comparing the classification ofteratogen or non-teratogen within the common treatments of eachcomparison.

Results

Phase 1 Model Confirmation and Characterization of MetabolitesPredictive of Developmental Toxicity. The first phase of this study wasconducted to confirm the predictivity of individual metabolites.Characterization of the predictive metabolites led to the development ofthe new targeted biomarker assay described in the second phase of thisstudy. Previously, a training set of 23 pharmaceutical compounds (Table2) was utilized to identify a metabolic signature capable of predictingteratogenicity in vitro (Kleinstreuer et al., 2011, Toxicol ApplPharmacol; 257:111-121). The metabolites that exhibited a statisticallysignificant change upon treatment with teratogens, and lacked a responsein non-teratogens, were characterized for their ability to classifydevelopmental toxicants using a simple fold change threshold. Of thesemetabolites, ornithine and cystine were identified as metabolites thatare representative of the previously applied metabolic signature thatwas highly predictive of developmental toxicity. The capacity of each ofthese two metabolites to classify developmental toxicants wascharacterized by determining a teratogenicity threshold based on thefold change of cells treated with a test compound versus the referencetreatment (0.1% DMSO) of each metabolite. The threshold was used toevaluate the classification accuracy of each metabolite within thetraining set.

Ornithine and cystine each exhibited characteristics amenable to rapidevaluation of the potential for a test compound to perturb metabolism inmanner consistent with teratogenicity. Both metabolites are highlyabundant in spent cell culture media from hES cells and show changes intheir abundance in response to treatment that were reproducibly measuredon multiple LC-HRMS instruments. To confirm these initial observations,and the reproducibility of the approach, the metabolites were furtherevaluated in a study that encompassed 9 independent experimentalreplications (blocks) of the training set. The secreted metaboliteornithine was able to distinguish teratogens from non-teratogens with83% accuracy (Table 5) using a two-sided threshold consisting of eitheran 18.5% decrease or 20% increase in accumulation of ornithine (FIG.4A). Cystine (a media constituent) was the most predictive individualmetabolite in classifying teratogens and had an accuracy of 83% (Table5) using a threshold of a 10% increase relative to the referencetreatment (FIG. 4B). Cystine exhibits a significant increase inabundance relative to the reference treatment for most of the teratogensthat did not cause cytotoxicity in hES cells (such as hydroxyurea,all-trans retinoic acid, 13-cis retinoic acid, carbamazepine, andthalidomide). Ornithine decreased with cytotoxic treatments

(such as 5-fluorouracil, cytosine arabinoside, methotrexate, andvalproic acid) but increased when cells were exposed to the relatednon-cytotoxic teratogens all-trans retinoic acid and 13-cis retinoicacid.

Next, the possibility that the fold changes in the ratio of ornithineand cystine would be more predictive than their individual fold changeswas evaluated. When the ornithine fold change was divided by the cystinefold change (i.e., the o/c ratio), the resulting ratio was able tocorrectly classify 91% (Table 5) of the training set (FIG. 4C) using ateratogenicity threshold of a 12% decrease in the o/c ratio,misclassifying only diphenylhydantoin and warfarin. Compared to theaccuracy of ornithine and cystine alone, application of the o/c ratioincreased the overall prediction accuracy by 8%, capturing the highspecificity of ornithine and high sensitivity of cystine (Table 5)yielding a more accurate classification of teratogenicity.

TABLE 4 Teratogenicity Threshold and Metabolite Model Metrics in theUntargeted Metabolomics-Based Developmental Toxicity Assay.Teratogenicity Metabolite Threshold Accuracy Sensitivity SpecificityOrnithine ≦81.5% or ≧120% 0.83 0.67 1.00 Cystine ≧110% 0.83 0.83 0.82Ornithine/ ≦88% 0.91 0.83 1.00 Cystine Teratogenicity Threshold, Acritical threshold of metabolic perturbation that is associated withteratogenesis; Accuracy, number of correct predictions divided by thenumber test compounds evaluated; Sensitivity, Detection of teratogens;Specificity, Detection of non-teratogens.Phase 2 Development and Evaluation of a Targeted Biomarker Assay toPredict Developmental Toxicity Associated with Exposure.

Targeted LC-HRMS Method Development. In the second phase of this study,a targeted biomarker-based assay was developed using the metabolitesconfirmed in Phase 1. Since toxicity is a function of both the chemicalagent and exposure level, the high level of predictivity associated witha threshold of toxicity of the o/c ratio provided an opportunity fordevelopment of a targeted, rapid, teratogenicity assay. To that end, ashort and reproducible analysis method was developed and optimized forfast-turnaround analysis of relative changes in ornithine and cystineabundance in hES cell spent media samples. In contrast, the untargetedmetabolomic methods that had been previously used were designed toanalyze a wider breadth of small molecules, and thus required a lengthychromatographic separation. The prior platform also depended upon twodata acquisitions for each sample, in positive and negative ionizationmodes. Focusing on the chromatographic separation, ionization anddetection of ornithine and cystine only, a new, targeted method wasdesigned specifically to more rapidly measure the relative changes ofthese metabolites observed in the hES cell model system. The newUPLC-HRMS method was developed and assessed using spent media samples(prepared as previously described) for added speed, sensitivity, andretention time reproducibility for measurements of ornithine andcystine. This resulted in a significant reduction in assay turn-aroundtime. The data acquisition time for each sample was reduced from 23 to6.5 minutes, providing a four-fold increase in LC-HRMS throughput. Thepositive ionization mode was preferentially amenable for detection ofthese metabolites, thereby eliminating the need for the negative mode,which further reduced the total analysis time by half for each samplebatch, thus increasing total instrument throughput eight-fold. Methodreproducibility was evaluated across 17 batches performed over 120 daysusing reference treatment samples (DMSO treated cells). The average CVfor the integrated area of the internal standards and endogenousmetabolites was <5% and <8%, respectively, demonstrating that the methodperforms in a reproducible manner.

Identification of the Teratogenicity Threshold. Based on the highclassification accuracy achieved in Phase 1 using a definedteratogenicity threshold, a 9-point concentration curve was used toclassify developmental toxicity potential based on a range of exposures.The teratogenicity threshold was optimized using the Phase 2 trainingset data by selecting a threshold that produced the highest accuracy ofprediction with the greatest sensitivity. The predicted teratogenicitypotential concentration was compared to the therapeutic C_(max) to scorethe performance and classification accuracy of this new assay design(described in FIG. 3, Table 6). With this approach, a 12% decrease inthe o/c ratio relative to the reference treatment was the optimumthreshold and was able to classify the training set of compounds with96% accuracy (Table 7, FIG. 5A). The assay correctly classified all thenon-teratogens (100% specificity) and misclassified only one of theknown human development toxicants, diphenylhydantoin (92% sensitivity).

Evaluation of the Targeted Biomarker Assay Performance based on the TestSet Predictions. The teratogenicity threshold identified using thetraining set was applied to the test set of compounds to assess thepredictivity of the targeted biomarker assay developed in this study.The test set consisted of 13 compounds not included in the training setwith known human teratogenicity, having FDA pregnancy classifications ofB, D and X. The teratogenicity potential concentration of each compoundfor the o/c ratio was scored against the compound's therapeutic C_(max).The test set was classified with 77% accuracy (100% specificity, 57%sensitivity, Table 7). The o/c ratio incorrectly classified theteratogens bosentan, lapatinib and lovastatin (Table 8, FIG. 5B). Pleasenote that the C_(max) for everolimus is below the lowest exposure levelused in the assay and the o/c ratio for this compound begins below theteratogenicity threshold, so it is classified as a teratogen even thoughit groups with the non-teratogens in FIG. 5B.

TABLE 5 Targeted Biomarker Assay Results: Training Set. C_(max)Teratogenicity Potential (μM) O/C Ratio Viability C_(max) Compound (μM)O/C Ratio Cell Viability Prediction Prediction Ref. Non-TeratogensAscorbic Acid 90 >300 >300 NON NON a Caffeine 9.3 >300 >300 NON NON bDiphenhydramine 0.25 1.8 78.9 NON NON c Doxylamine 0.38 12.9 >300 NONNON c Folic Acid 0.035 >300 >300 NON NON d Isoniazid 51 165.4 >300 NONNON e Levothyroxine 0.14 43.5 >300 NON NON f Penicillin G134.6 >300 >300 NON NON g Retinol 2.4 42.2 42.8 NON NON h Saccharin1.4 >300 >300 NON NON i Thiamine 0.67 >300 >300 NON NON j Teratogens13-cis Retinoic 2.9 0.0007 >300 TER NON k Acid 5-Fluorouracil 4.25 3 2TER TER l All-trans Retinoic 1.2 0.00004 114.5 TER NON m Acid Busulfan49.6 0.6 3 TER TER n Carbamazepine 47 0.9 >300 TER NON o Cytosine 0.60.04 0.1 TER TER p Arabinoside Diphenylhydantoin 79.3 263.3 288.7 NONNON q Hydroxyurea 565 5 251.6 TER TER r Methotrexate 0.2 0.05 0.05 TERTER s Thalidomide 12.4 0.2 >300 TER NON t Valproic Acid 1000 90.8 1113.7TER NON u Warfarin 23.4 6.5 >300 TER NON v C_(max), therapeutic peakplasma in vivo concentration; Teratogenicity Potential, interpolatedconcentration when the dose response curve of the o/c ratio or cellviability crosses the teratogenicity threshold; NON, potentialnon-teratogen; TER, potential teratogen. Teratogenicity potential valuesfor the o/c ratio and viability measurements that occur at an exposurelevel below the C_(max) value are bolded. a Padayatty et al., 2004, AnnIntern Med; 140: 533-537. b Caffeine Pharmacology (see worldwide web atreference.medscape.com/drug/cafcit-nodoz-caffeine-342995#10). c Luna etal., 1989, J Clin Pharmacol; 29: 257-260. d Ubeda et al., 2011,Nutrition; 27: 925-930. e Isoniazid (systemic), (see the worldwide webat drugs.com/mmx/isoniazid.html). f Briggs et al., 2011, “Drugs inpregnancy and lactation,” 9th ed. Philadelphia: Lippincott Williams &Wilkins. g Penicillin G Potassium Injection (Product Information, 2012),Baxter Healthcare, Deerfield, Illinois. h Aquasol A (ProductInformation), Mayne Pharma, Paramus, New Jersey. i Vaisman et al., 2001,Arzneimittelforschung; 51: 246-252. j Drewe et al., 2003, J Clin PharmTher; 28: 47-51. k Accutane (Product Information, 2010), RocheLaboratories, Nutley, New Jersey. l Oman et al., 2005, Cancer ChemotherPharmacol; 56: 603-609. m Muindi et al., 1992, Cancer Res; 52:2138-2142. n Busulfex (Product Information, 2011), Otsuka AmericaPharmaceutical, Rockville, Maryland. o Mahmood and Chamberlin, 1998, BrJ Clin Pharmacol; 45: 241-246. p Weinstein et al., 1982, Blood; 59:1351-1353. q Dilantin (Product Information, 2012), Pfizer, New York, NewYork. r Liebelt et al., 2007, Birth Defects Res B Dev Reprod Toxicol;80: 259-366. s Shoda et al., 2007, Mod Rheumatol; 17:311-316. tThalidomide Pharmacology (see the worldwide web atreference.medscape.com/drug/thalomid-thalidomide-343211#10). u Depacon(Product Information, 2013), AbbVie, North Chicago, Illinois. vWelle-Watne et al., 1980, Medd Norsk Farm Selsk; 42: 103-114.

TABLE 6 Model Metrics of the Ornithine/Cystine Ratio Compared to CellViability from the Targeted Biomarker Assay. Assay Accuracy SensitivitySpecificity Training Set O/C Ratio 0.96 0.92 1.00 Cell Viability 0.700.42 1.00 Test Set O/C Ratio 0.77 0.57 1.00 Cell Viability 0.62 0.291.00 Accuracy, number of correct predictions divided by the number testcompounds evaluated; Sensitivity, Detection of teratogens; Specificity,Detection of non-teratogens.

TABLE 7 Targeted Biomarker Assay Results: Test Set. C_(max)Teratogenicity Potential (μM) O/C Ratio Viability C_(max) Compound (μM)O/C Ratio Cell Viability Prediction Prediction Ref. Non-TeratogensAcetaminophen 116.4 >300 >300 NON NON a Acycloguanosine 3 95.8 >300 NONNON b Amoxicillin 20.5 >300 >300 NON NON c Loratadine 0.03 37.8 76.3 NONNON d Metoclopramide 0.15 190.8 >300 NON NON e Sitagliptin 0.9522.6 >300 NON NON f Teratogens Aminopterin 0.3 0.01 0.01 TER TER gBosentan 2 44.9 221.9 NON NON h D-Penicillamine 13.4 <0.04 >300 TER NONi Everolimus 0.02 <0.04 5.2 TER NON j Lapatinib 4.2 29 20.8 NON NON kLovastatin 0.02 1.3 4.1 NON NON l ThioTEPA 7 0.04 0.5 TER TER m C_(max),therapeutic peak plasma in vivo concentration; Teratogenicity Potential,interpolated concentration when the dose response curve of the o/c ratioor cell viability crosses the teratogenicity threshold; NON, potentialnon-teratogen; TER, potential teratogen. Teratogenicity potential valuesfor the o/c ratio and viability measurements that occur at an exposurelevel below the C_(max) value are bolded. a Tylenol (ProductInformation, 2010), McNeil Consumer Healthcare, Fort Washington,Pennsylvania. b Palma-Aguirre et al., 2007, Clin Ther; 29: 1146-1152. cAmoxil (Product Information, 2011), Dr Reddy's Laboratories,Bridgewater, New Jersey. d Hilbert et al., 1987, J Clin Pharmacol; 27:694-698. e Leucuta et al., 2004, Rom J Gastroenterol; 13: 211-214. fJanuvia (Product Information, 2013), Merck, Whitehouse Station, NewJersey. g Cole et al., 2005, Clin Cancer Res; 11: 8089-8096. h vanGiersbergen et al., 2007, Clin Pharmacol Ther, 81: 414-419. i Cuprimine(Product Information. 2004), Merck, Whitehouse Station, New Jersey. jEverolimus (Product Information, 2011), Novartis Sverige A B, Täby,Sweden. k Tykerb (Product Information, 2013), GlaxoSmithKline, ResearchTriangle Park, North Carolina. l Altoprev (Product Information, 2012),Andrx Labs, Fort Lauderdale, Florida. m Thiotepa (Product Information,2001), Bedford Laboratories, Bedford, Ohio.

Comparison of the Ornithine/Cystine Ratio and Cell Viability. Becausethe metabolites that make up the o/c ratio are measured in spent cellculture media, the treated cells were available to perform cellviability analysis. The cell viability results were compared to the o/cratio to determine if the change in the ratio was due to cell death orif it was due to metabolic changes unrelated to changes in cellviability. The viability results were evaluated to determineclassification performance using an approach similar to the o/c ratio(FIG. 3). The teratogenicity threshold that was determined using the o/cratio results from the training set was also used to classifyteratogenicity by cell viability based on the interpolated concentrationat which the cell viability dose response curve exceeds theteratogenicity threshold (Tables 6 and 8). This enabled a directcomparison of the o/c ratio and cell viability at equal levels of changefrom controls. Cell viability had an accuracy of 70% for the trainingset and 62% for the test set (Table 7). The cell viability assay wassuccessful in correctly classifying all of the non-teratogens in boththe training and test sets but performed poorly for the classificationof teratogens, correctly classifying only 5 of the 12 compounds in thetraining set (42% sensitivity, Table 7) and 2 of the 7 teratogens in thetest set (29% sensitivity, Table 7). Those that were correctlyclassified by cell viability are antineoplastic compounds that killdividing cells.

When applied to the training and test sets, the o/c ratio was 26% and15% more accurate, respectively, than viability alone for the predictionof development toxicity (Table 7). Both the o/c ratio and cell viabilityassay correctly classify non-teratogens with respect to the C_(max)having 100% specificity, however they differ in their ability todiscriminate teratogens (Table 7). The o/c ratio is 50% more sensitivein the detection of teratogens than viability alone in the training setand 28% more sensitive in the test set (Table 7). Additionally, the o/cratio is able to classify both cytotoxic and non-cytotoxic teratogenscorrectly. The decrease in false negatives provided by the o/c ratio isrelated to the assay's measurement of metabolic perturbation that canoccur independent of changes in cell viability.

Highlighted in FIG. 6 is a subset of the results that demonstrateseveral characteristics of the assay with respect to the o/c ratioperformance relative to cell viability. Thalidomide (FIG. 6A) andall-trans retinoic acid (FIG. 6B) are examples of teratogens thatexhibit a change in the o/c ratio indicative of developmental toxicityin the absence of cytotoxicity. The teratogen valproic acid (FIG. 6C) isan example of a cytotoxic teratogen that causes a marked change in theo/c ratio at exposure levels well before cytotoxicity is observed.5-fluorouracil (FIG. 6D) is an antineoplastic teratogen that yields achange in o/c ratio that is directly correlated with a decrease in cellviability and the change in the metabolite ratio is likely a directresult of cell death. Retinol (FIG. 6E) is an example of a cytotoxicnon-teratogen where the o/c ratio is directly correlated with cell deathat exposure levels almost 20 times higher than those normallyencountered by humans. The non-teratogen saccharin (FIG. 6F) is acompound that yields no change in the o/c ratio or viability at theexposures examined in this study.

Application of the O/C Ratio to Compounds with Unknown HumanTeratogenicity. The targeted biomarker assay was applied to anapplication set of 10 compounds that have unknown human developmentaltoxicity outcomes. Since the human developmental toxicity of thesecompounds is unknown, the C_(max) approach (illustrated in FIG. 3) toscore assay performance was not applied and the compounds were treatedas unknowns, as is illustrated in FIG. 2. The results are presented asthey would be generated by the assay utilized in an industrial setting.The teratogenicity potential concentrations for the o/c ratio and cellviability are summarized in Table 9. All 10 compounds exhibited a changein the o/c ratio indicative of teratogenicity, although concentration atwhich this change occurred varied greatly between compounds. Nine of the10 compounds exhibited a change in cell viability within the exposurerange tested (Table 9). Seven of the 10 compounds caused a change in theo/c ratio prior to or in the absence of cytotoxicity (bolded compounds,Table 9). Rodent developmental toxicity testing identified a teratogenicand/or embryotoxic effect in seven of the 10 compounds in the absence ofmaternal toxicity. The other three compounds (adefovir dipivoxil,cidofovir, and ramelteon) were only embryotoxic at exposure levels thatalso caused maternal toxicity so it is unknown if the effect was due tocompound exposure.

TABLE 8 Targeted Biomarker Assay Results: Application Set. C_(max)Teratogenicity Potential (μM) Rodent in vivo test results^(a) C_(max)Compound (μM) O/C Ratio Cell Viability Teratogenic^(b) Embryotoxic^(c)Ref. 6-Aminonicotinamide NA <0.04 24.5  +^(d)  −^(d) NA Abacavir 14.995.1 94.1 + + i Adefovir dipivoxil^(e) 0.03 0.0015 0.02 − − j Amprenavir15.1 236.9 259.5 + + k Artesunate 73.9 0.64 0.58  +^(f)  +^(f) lCidofovir^(g) 41.2 0.3 1.9 − − m Entacapone 3.9 6.7 127 + − n Fluoxetine0.04 25.1 23 − + o Ramelteon^(h) 0.02 34 >300 − − p Rosiglitazone 1.718.9 21.8 − + q C_(max), peak plasma concentration in humans;Teratogenicity Potential, interpolated concentration when the doseresponse curve of the o/c ratio or cell viability crosses theteratogenicity threshold; NA, not available or undetermined.Teratogenicity potential values for the o/c ratio that occur before cellviability are bolded. ^(a)Data was compiled from Briggs et al. (2011,“Drugs in pregnancy and lactation,” 9th ed. Philadelphia: LippincottWilliams & Wilkins) unless otherwise noted. ^(b)A test compound wasconsidered teratogenic if it caused structural malformations in theabsence of maternal toxicity. ^(c)This column refers to an embryotoxiceffect in the absence of teratogenic effects. A test compound wasconsidered embryotoxic if it caused growth retardation or embryolethality in the absence of maternal toxicity. ^(d)Shepard and Lemire,2007, “Catalog of teratogenic agents,” 12th ed. Baltimore: The JohnsHopkins University Press. ^(e)Adefovir dipivoxil was teratogenic andembryotoxic at maternally toxic doses. ^(f)Clark, 2009, Reprod Toxicol;28: 285-296; and Shepard and Lemire, 2007, “Catalog of teratogenicagents,” 12th ed. Baltimore: The Johns Hopkins University Press.^(g)Cidofovir was embryotoxic at maternally toxic doses. ^(h)Ramelteonwas teratogenic at maternally toxic doses. i Ziagen (ProductInformation, 2012), GlaxoSmithKline, Research Triangle Park, NorthCarolina. j Hepsera (Product Information, 2012), Gilead Sciences, FosterCity, California. k Agenerase (Product Information, 2005),GlaxoSmithKline, Research Triangle Park, North Carolina. l Miller etal., 2012, Malar J; 11: 255. m Vistide (Product Information 2000),Gilead Sciences, Foster City, California. n Comtan (Product Information,2010), Novartis Pharmaceuticals, East Hanover, New Jersey. o Sarafem(Product Information, 2013), Warner Chilcott, Rockaway, New Jersey. pKarim et al., 2006, J Clin Pharmacol; 46: 140-148. q Avandia (ProductInformation, 2011), GlaxoSmithKline, Research Triangle Park, NorthCarolina.

Assay Performance (Comparison to Other Assays). The developmentaltoxicity predictions based on the o/c ratio for the training and testsets were compared to published results from other model systems (Table10). The developmental toxicity predictions from the model systemspresented in Table 10 for the application set are summarized inSupplementary Table 1. For the combined 36 training and test setcompounds, comparisons were made on a model system-by-system basis usingonly the treatments evaluated in both the targeted biomarker assay andeach model system it was being compared to. The results of thecomparisons (Table 11) indicate that the o/c ratio described here is amore accurate predictor of human developmental toxicants than the othermodel systems considered. The increase in accuracy is due to a lowerfalse positive rate (increased specificity) of the o/c ratio in eachcomparison with significant increase in specificity over other in vitrosystems such as mEST and WEC, as well as a moderate gain in sensitivity.Interestingly, the o/c ratio is able to correctly classify thenon-teratogens caffeine and retinol and teratogens warfarin andD-penicillamine, where the majority of other model systems fail. Thereis a high degree of concordance (≧75%) between the teratogenicityprediction of the o/c ratio and the in vivo rodent and rabbit models aswell as the ZET (Table 11). Concordance is lower between the o/c ratioand the mEST and WEC (67% and 69%, respectively, Table 11). The reasonfor lower concordance between the o/c ratio and these in vitro models isdue to the high accuracy of the targeted biomarker assay.

TABLE 9 Comparison of Targeted Biomarker Assay Results to PublishedDevelopmental Toxicity Assay Results: Training and Test Set. TargetedBiomarker Compound Humans^(a) Assay Rodent^(a) Rabbit^(a) mEST ZET WECAcetaminophen NON NON NON NA NA NON^(e) TER ^(k) Acycloguanosine NON NONTER NON NA NA TER ^(l) Amoxicillin NON NON NON NA NA NA NA Ascorbic AcidNON NON NON NA NON^(b) NON^(c, d, e) NON^(f) Caffeine NON NON TER TERTER ^(b) TER ^(e) TER ^(o) Diphenhydramine NON NON NON NON TER ^(b) TER^(e) NON^(f) Doxylamine NON NON NON NON TER ^(m) NA NON^(f) Folic AcidNON NON NON^(g) NA NA NA NON^(h) Isoniazid NON NON NON NON NON^(b, i)NON^(c, n) TER ^(f, j) Levothyroxine NON NON NON NON NA NA NA LoratadineNON NON NON NON NON^(i) TER ^(d) NON^(f, j) Metoclopramide NON NON NONNON TER ^(i. m) NON^(d) NON^(f, j) Penicillin G NON NON NON NONNON^(b, i) NON^(c, e, n) NON^(f, j) Retinol NON NON TER TER NON^(p) TER^(c, n) TER ^(q) Saccharin NON NON NON NON NON^(b, i) NON^(c, e) NON^(j)Sitagliptin NON NON TER NON NA NA NA Thiamine NON NON NA NA NA NA NA13-cis Retinoic TER TER TER TER TER^(p) TER^(r) TER^(s) 5-FluorouracilTER TER TER TER TER^(b, i) TER^(c) TER^(f, k) All-trans Retinoic TER TERTER TER TER^(b, p) TER^(c, e, r) TER^(q, s) Aminopterin TER TER TER TERNA NA NA Bosentan TER NON TER NON NA NA NA Busulfan TER TER TER TERTER^(i) NA TER^(j) Carbamazepine TER TER TER NA TER^(i) TER^(t) TER^(j)Cytosine TER TER TER NA TER^(i) TER^(n) TER^(j) Diphenylhydantoi TER NONTER TER TER^(b, i) NON ^(n) TER^(f, j) D-Penicillamine TER TER TER NANON ^(m) NON ^(d) NON ^(f) Everolimus TER TER TER NON NA NA NAHydroxyurea TER TER TER TER TER^(b, i) TER^(c) TER^(f, j) Lapatinib TERNON TER TER NA NA NA Lovastatin TER NON TER NON TER^(m) TER^(d) NAMethotrexate TER TER TER TER TER^(b, i) TER^(d) TER^(f) Thalidomide TERTER NON ^(u) TER NA TER^(d) TER^(f) ThioTEPA TER TER TER TER NA TER^(v)NA Valproic Acid TER TER TER TER^(u) TER^(b, i) TER^(e, n) TER^(f, j)Warfarin TER TER TER NON NON^(i, m) TER^(d) NON ^(j) mEST, mouseembryonic stem cell test; ZET, zebrafish embryotoxicity test; WEC, wholeembryo culture; NON, non-teratogen; TER, teratogen; NA, not available.If there were conflicting predictions, the classification from the morerecent publication or with more publications in agreement was used.Bolded results indicate predictions that differ from known humandevelopmental toxicity effects. ^(a)Human, rodent and rabbit effectssummarized from Drugs in Pregnancy and Lactation (Briggs et al., 2011,“Drugs in pregnancy and lactation,” 9th ed. Philadelphia: LippincottWilliams & Wilkins); TERIS and/or the ACToR database (on the World WideWeb at actor.epa.gov/actor/faces/ACToRHome.jsp) unless otherwise noted.^(b)Genschow et al., 2004, Altern Lab Anim; 32: 209-244. ^(c)Brannen etal., 2010, Birth Defects Res B Dev Reprod Toxicol; 89: 66-77.^(d)Gustafson et al., 2012, Reprod Toxicol; 33: 155-164.^(e)Selderslaghs et al., 2012, Reprod Toxicol: 33: 142-154. ^(f)Zhang etal., 2012, Toxicol Sci; 127: 535-546. ^(g)Hansen et al, 1993,Teratology; 47: 420. ^(h)Hansen, 1995, Teratology; 51: 12A ^(i)Paquetteet al., 2008, Birth Defects Res B Dev Reprod Toxicol; 83: 104-111.^(j)Thomson et al., 2011, Birth Defects Res B Dev Reprod Toxicol; 92:111-121. ^(k)Stark et al., 1990, J Pharmacol Exp Ther; 255: 74-82.^(l)Klug et al., 1985, Arch Toxicol; 58: 89-96. ^(m)Marx-Stoelting etal., 2009, Altern Lab Anim; 37: 313-328. ^(n)McGrath and Li, 2008, DrugDiscov Today; 13: 394-401. ^(o)Robinson et al., 2010, Toxicol Sci; 118:675-685. ^(p)Louisse et al., 2011, Toxicol Lett; 203: 1-8. ^(q)Ritchieet al., 2003, Birth Defects Res A Clin Mol Teratol; 67: 444-451.^(r)Herrmann, 1995, Toxicol In Vitro; 9: 267-283. ^(s)Klug et al., 1989,Arch Toxicol; 63: 185-192. ^(t)Madureira et al., 2011, Environ ToxicolPharmacol; 32: 212-217. ^(u)Jelovsek et al., 1989, Obset Gynecol; 74:624-636. ^(v)Weigt et al., 2011, Toxicology; 281: 25-36.

TABLE 10 Model Metrics of the Targeted Biomarker Assay PredictionsCompared to Other Model Predictions Based on Treatments in Common. ModelSystem N Concordance Acc TB_Acc Sen TB_Sen Spec TB_Spec Targeted 36 NA0.89 NA 0.79 NA 1.00 NA Biomarker Assay Rodent 35 0.74 0.86 0.89 0.950.79 0.75 1.00 Rabbit 28 0.79 0.79 0.86 0.75 0.75 0.83 1.00 mEST 23 0.650.74 0.91 0.85 0.85 0.60 1.00 ZET 24 0.75 0.75 0.92 0.86 0.86 0.60 1.00WEC 26 0.69 0.73 0.96 0.85 0.92 0.62 1.00 N, The number of treatmentsassayed that were common between the model system and the targetedbiomarker assay; TB, the targeted biomarker assay results using thetreatments evaluated in that model system; Acc, Accuracy of modelsystem; TB_Acc, Accuracy of targeted biomarker assay; Sen, Sensitivityof model system; TB_Sen, Sensitivity of targeted biomarker assay; Spec,Specificity of the model system; TB_Sen, Specificity of the targetedbiomarker assay.

TABLE 11 Comparison of Targeted Biomarker Assay Results to PublishedDevelopmental Toxicity Assay Results: Application Set. TargetedBiomarker Compound Humans^(a) Assay^(b) Rodent^(a) Rabbit^(a) mEST ZETWEC 6-Aminonicotinamide NA TER TER TER TER^(c) NA TER^(d) Abacavir NANON TER NON NA NA NA Adefovir dipivoxil NA TER NON NON NA NA NAAmprenavir NA NON TER TER NA NA NA Artesunate NA TER TER TER NA NA NACidofovir NA TER NON NON NA NA NA Entacapone NA TER TER NON NA NA NAFluoxetine NA NON TER NON TER^(e) NA NON^(f, g) Ramelteon NA NON NON NONNA NA NA Rosiglitazone NA NON TER TER NA NA NON^(h) mEST, mouseembryonic stem cell test; ZET, zebrafish embryotoxicity test; WEC, wholeembryo culture; NON, non-teratogen; TER, teratogen; NA, not available.If there were conflicting calls, the classification from the more recentpublication or with more publications in agreement was used. ^(a)Human,rodent and rabbit effects summarized from Drugs in Pregnancy andLactation (Briggs et al., 2011, “Drugs in pregnancy and lactation,” 9thed. Philadelphia: Lippincott Williams & Wilkins), TERIS and/or the ACToRdatabase (on the World Wide Web atactor.epa.gov/actor/faces/ACToRHome.jsp) unless otherwise noted.^(b)Predictions for the targeted biomarker assay were made using thetherapeutic C_(max) when available as described in the methods sectionand illustrated in FIG. 3. However, in application of the assay thismethod will not be used as a C_(max) will not be available. ^(c)Genschowet al., 2004, Altern Lab Anim; 32: 209-244. ^(d)Piersma et al., 1995,Reprod Toxicol; 9: 275-280. ^(e)Paquette et al, 2008, Birth Defects ResB Dev Reprod Toxicol; 83: 104-111. ^(f)Thomson et al., 2011, BirthDefects Res B Dev Reprod Toxicol; 92: 111-121. ^(g)Zhang et al., 2012,Toxicol Sci; 127: 535-546. ^(h)Chan and Lau, 2006, Fertil Steril; 86:490-492.

Discussion

The present assay has been developed to address the need for moreaccurate, rapid, and less expensive alternatives to animal testing. Ourgoal was to provide toxicologists with a new and biologically germanetool to aid in compound prioritization prior to the currently requiredin vivo testing and as part of emerging multi-tiered testing strategies.Undifferentiated hES cells represent a simple and elegant test systemfor modeling a test compound's developmentally toxic effects on humancells at the very earliest stages of development, which in some casescan lead to implications of the compound's effects in later stage fetaldevelopment as well. A developmental toxicity test based on hES cellsreduces the risk of false-negatives due specifically to inter-speciesdifferences in developmental pathways and pharmacokinetics (Scott etal., 2013, Toxicol Lett; 219:49-58). The present example modifies anuntargeted metabolomics-based developmental toxicity assay to decreasecomplexity and increase throughput by focusing on two biologicallyrelevant metabolites that can accurately model human toxic response overa wide range of exposure levels.

This example demonstrates that a certain degree of metabolicperturbation can be used to predict a test compound's potential to causedevelopmental toxicity. The assay of this example uses a multi-exposureapproach that allows for a look at cellular response over a large rangeof exposure levels. Application of the teratogenicity threshold to thisapproach allowed the use of changes in metabolism at increasing exposurelevels to identify the concentration at which metabolism was altered ina manner indicative of potential teratogenicity. The model created hereallows the comparison of changes in a metabolic ratio of ornithine andcystine to cell viability to identify the exposure level where changesin metabolism are likely to lead to teratogenicity and relate it to celldeath. The combined evaluation of cell viability and changes inmetabolism allow this assay to also identify when exposure could lead todevelopmental toxicity due to cell death or possible embryo toxicity.The o/c ratio can discriminate between teratogens and non-teratogenswith a combined 89% accuracy in the training and test sets using theteratogenicity threshold set in Phase 2 (Table 11).

Analysis of metabolites is a critical process in understandingmechanisms of toxicity since metabolites play critical roles in themaintenance of homeostasis and signaling. Perturbation of individualmetabolites has the ability to disrupt normal developmental processes.Alterations in metabolite abundance can occur via mechanisms independentof protein and transcript abundance such as allosteric interaction of acompound or compound's metabolite with an enzyme, defects inpost-translational modification, disrupted protein-protein interactionsand/or altered transport. Changes in metabolism, as measured in thespent medium of cell culture systems, yield a distinguishable “metabolicfootprint,” which is a functional measure of cellular metabolism thatcan be used to evaluate response to treatment. The perturbation ofbiochemical pathways that contain ornithine and cystine as reactants orproducts have been experimentally associated with mechanisms ofteratogenesis. Extra-cellularly, or within the secretome measured by ourassays, cystine predominates over cysteine due to the oxidative state ofthe medium. Cystine is rapidly converted to cysteine once it is importedinto the intracellular environment and is part of the cystine/cysteinethiol redox couple, a critical component of a cell's regulatory capacityto handle reactive oxygen species (ROS). Its role has been investigatedwith regard to its capacity to modulate differentiation, proliferation,apoptosis, and other cellular events that may lead to teratogenesis(Hansen, 2006, Birth Defects Res C Embryo Today; 78:293-307). A broadspectrum of teratogens including pharmaceuticals, pesticides, andenvironmental contaminants are suspected of creating ROS or disruptingcellular mechanisms that maintain the appropriate balance of a cell'sredox state, which can lead to adverse effects on developmentalregulatory networks as a mechanism of action of developmental toxicity(Hansen, 2006, Birth Defects Res C Embryo Today; 78:293-307; Kovacic andSomanathan, 2006, Birth Defects Res C Embryo Today; 78:308-325). It hasbeen hypothesized that a major mechanism of thalidomide teratogenesisand its species specific manifestation of developmental toxicity isrelated to ROS related up-regulation of apoptotic pathways during limbformation (Hansen, 2006, Birth Defects Res C Embryo Today; 78:293-307).The measurement of cystine in this assay provides insight into a cell'sredox status. When cystine's uptake is perturbed, it can act as abiomarker, indicating a disruption in the cell's ability to signal usingROS related pathways.

The second metabolite in this assay is ornithine, which is secreted bythe hES cells during culture. Ornithine is formed as a product of thecatabolism of arginine into urea, is critical to the excretion ofnitrogen, and is a precursor to polyamines. Catabolism of ornithine isimpacted by the teratogen all-trans retinoic acid, which is a suppressorof the transcription of ornithine decarboxylase (ODC), leading toincreased ornithine secretion which in turn inhibits polyamine synthesis(Mao et al., 1993, Biochem J; 295:641-644). It is also clear that ODCplays an important role in development, since a mouse model with ODCknocked out leads to disruption of very early embryonic stages and islethal to the developing embryo (Pegg, 2009, IUBMB Life; 61:880-894).Alterations in ornithine levels could lead to the disruption inpolyamine metabolism, which is critical for cellular growth anddifferentiation during human development (Kalhan and Bier, 2008, AnnuRev Nutr; 28:389-410).

Only one of the 23 compounds in the training set (diphenylhydantoin) andthree of the 13 compounds in the test set (bosentan, lapatinib, andlovastatin) were misclassified in the targeted biomarker assay (Tables 6and 8). All four of these compounds exhibited a change in the o/c ratioindicative of teratogenicity; however the teratogenicity potentialconcentration is higher than the therapeutic C_(max), which was set as amarker of biological relevance for exposure level. For discoverycompounds that will not have an established C_(max) value, these changesin the o/c ratio can be used as a signal regarding the teratogenicpotential of the compound. While epidemiological studies have shown anassociation between diphenylhydantoin and birth defects, there have beenno such studies describing the incidence of birth defects followingbosentan, lapatinib and lovastatin exposure during pregnancy. No casereports have been published regarding birth defects in infants exposedto bosentan or lapatinib during pregnancy and only a handful of reportsdescribing malformations following lovastatin exposure during earlypregnancy (TERIS).

In vivo rat developmental toxicity studies have identified a lowestobserved adverse effect level (LOAEL) for lovastatin of 100 mg/kg bodyweight per day during organogenesis (Lankas et al., 2004, Birth DefectsRes B Dev Reprod Toxicol; 71:111-123). Interestingly, this level ofexposure results in a C_(max) around 1.5 μM (Lankas et al., 2004, BirthDefects Res B Dev Reprod Toxicol; 71:111-123), which is close to theteratogenicity potential identified by the o/c ratio in this study (1.3μM, Table 7, FIG. 7A). Lapatinib causes rat pup mortality in vivo whengiven during organogenesis at exposure levels that are about 3.3 timesthe human clinical exposure based on AUC (Briggs G G, Freeman R K, YaffeS J, 2011, “Drugs in pregnancy and lactation,” 9th ed. Philadelphia:Lippincott Williams & Wilkins). This level of exposure is approximatelyequal to the concentration where cell viability decreases in hES cellsfollowing lapatinib exposure (FIG. 7B). Animal models are currently usedto measure teratogenicity risk but it is still unknown how well theirresults correlate to human risk for individual compounds. While theprimary goal of the assay is to predict potential for teratogenicity inhumans, it is also important to understand concordance with in vivoanimal models used for regulatory acceptance. These are a few examplesof how the data generated in the targeted biomarker assay can becorrelated to in vivo developmental toxicity data.

For the compounds evaluated in this study, the targeted biomarker assayagrees with in vivo rodent and rabbit studies about 75% of the time(Table 11). There is still significant opportunity to improve theunderstanding of how to translate compound concentrations from in vitrosystems to human exposure levels (Bhattacharya et al., 2011, PLoS One;6:e20887). The application set was used to demonstrate how themeasurement of toxicity potential across an exposure range can put modelresponse into perspective in terms of the overall compound risk whencombined with additional assays conducted during a compound's discoveryand development. The 10 compounds in this set have unknown humandevelopmental toxicity outcomes, as would any novel compound. The o/cratio was compared with the available C_(max) for the application set ofcompounds to begin to assess the relevance of the signal ofteratogenicity potential for each compound (Supplementary Table 1). Thetherapeutic C_(max) was used to understand the potential exposure levelencountered in humans. However, since the human teratogenicity of thesecompounds is unknown, the C_(max) was not used to assess thepredictivity of the assay. The application set was meant to demonstrateutility of the targeted biomarker assay for unknown compounds incontrast to assessment of assay performance for compounds with knownhuman teratogenicity (FIG. 8). Any available preclinical in vivofindings were then used to develop and understanding of each compoundand its risk potential. Such an approach could be used in adoption ofthe assay as part of a traditional compound discovery or preclinicaldevelopment program, or as part of a new paradigm utilizing a panel ofhuman cell based assays aimed at early decision making.

A significant advantage of the targeted biomarker assay is the use ofhuman cells, derived from an embryo, which are able to recapitulateevery cell type in the body and have an unlimited capacity toproliferate in culture. The possibility of species-specific differencesin developmental toxicity that may be observed in other in vitrodevelopmental toxicity assays is eliminated. In contrast to theECVAM-evaluated mEST, the assay presented here does not requiredifferentiation of the hES cells into specific lineages such as embryobodies or cardiomyocytes. Differentiation into specific lineages maylimit an assay's potential for predicting teratogens that affect adifferent developmental lineage. The assay described herein cancorrectly classify compounds that are known to affect multiple lineages,including cardiovascular, neural and skeletal (Tables 2 and 3). Thetargeted biomarker assay provides endpoints which are determinedanalytically and do not need any subjective interpretation ofmorphology, as is required by the mEST, post-implantation rat WEC testand ZET. Recent modifications to the mEST have begun to address theselimitations by adding additional developmental endpoints (i.e., neuraland osteoblast differentiation) and implementing molecular endpoints inplace of subjective evaluation (reviewed in Theunissen and Piersma,2012, Front Biosci; 17:1965-1975). Table 10 presents a comparison of theresults of the targeted biomarker assay described here and five otherdevelopmental toxicity assays; the targeted biomarker assay has a higheraccuracy than the other assays (Table 11). The higher accuracy of thepredictions made with the o/c ratio is due to an increase inspecificity, or the detection of non-teratogens, over the other assays.It is important to note that differences exist between each of the modelsystems in the way that compounds are predicted. None of the otherassays included in Table 10 classify compounds based on human exposurelevels, whereas our classification system directly compares a compound'steratogenicity potential to the known therapeutic C_(max) for compoundsthat have known human developmental toxicity outcomes. When makingpredictions, the actual exposure levels of a compound likely to beencountered by a fetus are critical. Nine of the 17 human non-teratogenstested in the targeted biomarker assay caused a change in the o/c ratioat exposure levels above the therapeutic C_(max). It is believed thatany compound, given at the right dose, at the right time duringdevelopment, in the right species will be teratogenic (Daston G P andKnudsen T B, 2010, “Fundamental concepts, current regulatory design andinterpretation,” In: Knudsen T B, Daston G P, editors. ComprehensiveToxicology. Vol 12, 2nd ed. New York: Elsevier. p 3-9). The ability ofthe targeted biomarker assay to separate exposure levels that are notindicative of teratogenicity from levels that are indicative ofteratogenicity is a key strength of the assay.

Although the targeted biomarker assay described herein shows significantpromise in predicting developmental toxicity, hES cells, as with otherin vitro models, cannot fully reproduce all events contributing to thedisruption of normal human development by exogenous chemicals. In vitromodels of toxicity do not include the effects of absorption,distribution, metabolism and excretion (ADME), which may make itdifficult to predict how a substance of unknown toxicity will act invivo. The absence of metabolic activity could partially be overcome bythe addition of an exogenous bioactivation system when metabolicactivation is required or to test both the parent compound and any knownmetabolites for developmental toxicity potential. Testing both parentcompounds and metabolites can help discern which agent is the proximateteratogen, which is essential to accurately predicting a test compound'sdevelopmental toxicity potential. Additionally, maternal-fetalinteractions and organogenesis cannot be modeled using an in vitromodel. However, one of the advantages of using an in vitro assay is theability to separate adverse outcomes due to compound versus outcomes dueto maternal toxicity from compound exposure. Developmental toxicitytesting in cells derived from human embryos is likely to generate morereliable in vitro prediction endpoints than endpoints currentlyavailable through the use of animal models, or other in vitro non-humanassays given the physiological relevance of hES cells to humandevelopment.

This assay can help reduce or eliminate species-specificmisinterpretations, reduce need for a second species, and could beincluded as part of a panel of in vitro assays aimed at defining wherepotential adverse responses in human populations may exist. Much likeother in vitro culture systems that are used to understand potential fortarget organ toxicity, this assay can assess potential for developmentaltoxicity. Part of its strength is that this is accomplished across arange of exposure levels. While there is no defined way to projectsafety margins or fully predict human response based on in vitro data,assays such as this one can help define exposure ranges where responsemay be expected as well as those where a response would not be expectedto occur. Results could then be incorporated into a panel of tests thatin aggregate develop an approximation of clinical safety margins. Thisinformation could help to drive decisions as to whether a compoundshould progress along its development path.

Example 1 has also published as Smith et al., 2013, “Establishment andassessment of a new human embryonic stem cell-based biomarker assay fordevelopmental toxicity screening,” Birth Defects Res B Dev ReprodToxicol; 98(4):343-63, which is hereby incorporated by reference in itsentirety.

Example 2 ADMA/Cystine Ratio

With the present invention, it has been determined that the analysis ofdata obtained from a small number of metabolites can serve as veryaccurate predictors of teratogenicity. As described in Example 1, analgorithm was developed that evaluated the individual predictivecapacity of these secreted features and media components with thetraining set to identify and confirm several key features that could beused to develop a much simplified predictive model. The selectionprocess weighted the predictive capacity of a feature, overallintensity, and peak shape to identify very well behavedfeatures/metabolites that could be measured by targeted LC-MS or even byother detection systems. Several pairs of features and some individualfeatures were identified that could accurately identify at least 90% ofthe teratogens and non-teratogens in the training and test sets thatwere used for the development of the devTOX computational models.

In this example, cystine and asymmetric dimethylarginine (ADMA) wereselected for the simplified predictive model due to their abundance,ideal peak shapes, and their exhibition of similar performance metricsas the computational model (Table 14) with both showing an accuracy of93%. This simplified model is based on a ratio of the referencetreatment (DMSO) normalized values of ADMA and cystine. This simpleratio is able to differentiate teratogens that generally exhibit adecrease in the ratio relative to non-teratogens. When evaluated across9 independent replications of the training set it is clearly able todifferentiate teratogens from non-teratogens (FIG. 9), using a criteriaof ratios less than 0.9 indicates teratogenicity.

FIG. 9 shows the ratio of the reference treatment normalized ratio ofADMA (secreted metabolite) and cystine (media constitute) for eachtraining set agent. The X-axis is the reference normalized ratio ofADMA/Cystine. The y-axis is the training set of pharmaceuticals. Greycolor with triangle glyphs represents teratogens and black color withcircle glyphs represents non-teratogens. Each glyph point represents themedia value of an independent experimental block (6 reps per block). Thecrosshair glyphs mark the sample medians. In FIG. 9, grey vertical lineis threshold of teratogenicity, grey horizontal lines are the medianabsolute deviations, and black vertical line designates 1.0. The arrowsat the bottom indicate the values used for differentiation of teratogensand nonteratogens, utilizing a cut off of 0.9 (grey line).

TABLE 12 Comparison of validation and test set model predictions.

Treatments not included in the training set marked with an asterisk anditalic. Ter = Teratogen, Non = Non-teratogen.

Example 3 Cystathionine/Cystine Ratio

Following procedures as described in the previous examples, it was alsodetermined the determination of cystathionine/cystine fold change ratiosalso provide excellent predictivity and general performance in the rapidteratogenicity screen described herein. This is shown in FIG. 10. InFIG. 10, grey color with triangle glyphs represents teratogens, blackcolor with circle glyphs represents non-teratogens, grey vertical lineis threshold of teratogenicity, crosshair glyphs mark the samplemedians, grey horizontal line is the median absolute deviations, andblack vertical line designates 1.0.

Example 4 Viability Analysis

Changes in cellular metabolism as measured in the spent medium followingcell culture (the secretome) is a functional measure of cell health. Thecell culture “secretome” refers to the metabolites present in the spentmedia or cell culture supernatant following cell culture. The secretomeis comprised of media components, metabolites passively and activelytransported across the plasma membrane, intracellular metabolitesrelease upon lysis, and those produced through extracellular metabolismof enzymes. The change in secretome elicited by an experimental agentrelative to untreated cultures produces a metabolic signature that canbe used to infer the number of metabolically viable cells present withina cell culture. We have identified a number of secreted metabolites thatcan be utilized to infer the number viable cells relative to the numberof cells in a reference culture “control group”. We compared a number ofsecreted metabolites to the results of viability analysis performedusing a commercial kit and discovered that a decrease in the relativeabundance of the secreted metabolites are directly correlated withmeasurements of cell viability with a Pearson correlation coefficientgreater than 0.86 (P value<<0.001) when cytotoxicity is observed in atleast the two highest concentrations of a 9 point concentration curve.These metabolites could be utilized by LC-MS or kit based detection todetermine the number of viable cells within a cell culture without arequirement to destroy or impact the cells. These metabolites can beused as novel measure of viability that does not require disrupting thegrowing cells.

The complete disclosure of all patents, patent applications, andpublications, and electronically available material (including, forinstance, nucleotide sequence submissions in, e.g., GenBank and RefSeq,and amino acid sequence submissions in, e.g., SwissProt, PIR, PRF, PDB,and translations from annotated coding regions in GenBank and RefSeq)cited herein are incorporated by reference. All headings are for theconvenience of the reader and should not be used to limit the meaning ofthe text that follows the heading, unless so specified. In the eventthat any inconsistency exists between the disclosure of the presentapplication and the disclosure(s) of any document incorporated herein byreference, the disclosure of the present application shall govern. Theforegoing detailed description and examples have been given for clarityof understanding only. No unnecessary limitations are to be understoodtherefrom. The invention is not limited to the exact details shown anddescribed, for variations obvious to one skilled in the art will beincluded within the invention defined by the claims.

1. A method of classifying a test compound as a teratogen or anon-teratogen, the method comprising: culturing undifferentiated humanstem cell-like cells (hSLCs) in the presence of the test compound and inthe absence of the test compound; determining the fold change inornithine, or fragment, adduct, deduct or loss thereof, in the culturemedia of undifferentiated hSLCs cultured in the presence of the testcompound in comparison with hSLCs cultured in the absence of the testcompound; determining the fold change in cystine, or fragment, adduct,deduct or loss thereof, in the culture media of undifferentiated hSLCscultured in the presence of the test compound in comparison with hSLCscultured in the absence of the test compound; determining the ratio ofthe fold change in ornithine, or fragment, adduct, deduct or lossthereof, to the fold change in cystine, or fragment, adduct, deduct orloss thereof, wherein: a ratio of less than or equal to about 0.88 isindicative of the teratogenicity of the test compound; and a ratio ofgreater than about 0.88 is indicative of the non-teratogenicity of thetest compound.
 2. A method of predicting teratogenicity of a testcompound, the method comprising: culturing undifferentiated human stemcell-like cells (hSLCs) in the presence of the test compound and in theabsence of the test compound; determining the fold change in ornithine,or fragment, adduct, deduct or loss thereof, in the culture media ofundifferentiated hSLCs cultured in the presence of the test compound incomparison with hSLCs cultured in the absence of the test compound;determining the fold change in cystine, or fragment, adduct, deduct orloss thereof, in the culture media of undifferentiated hSLCs cultured inthe presence of the test compound in comparison with hSLCs cultured inthe absence of the test compound; determining the ratio of the foldchange in ornithine, or fragment, adduct, deduct or loss thereof, to thefold change in cystine, or fragment, adduct, deduct or loss thereof,wherein: a ratio of less than or equal to about 0.88 is indicative ofthe teratogenicity of the test compound; and a ratio of greater thanabout 0.88 is indicative of the non-teratogenicity of the test compound.3. A method for validating a test compound as a teratogen, the methodcomprising: culturing undifferentiated human stem cell-like cells(hSLCs) in the presence of the test compound and in the absence of thetest compound; determining the fold change in ornithine, or fragment,adduct, deduct or loss thereof, in the culture media of undifferentiatedhSLCs cultured in the presence of the test compound in comparison withhSLCs cultured in the absence of the test compound; determining the foldchange in cystine, or fragment, adduct, deduct or loss thereof, in theculture media of undifferentiated hSLCs cultured in the presence of thetest compound in comparison with hSLCs cultured in the absence of thetest compound; determining the ratio of the fold change in ornithine, orfragment, adduct, deduct or loss thereof, to the fold change in cystine,or fragment, adduct, deduct or loss thereof, wherein: a ratio of lessthan or equal to about 0.88 is indicative of the teratogenicity of thetest compound; and a ratio of greater than about 0.88 is indicative ofthe non-teratogenicity of the test compound.
 4. A method for determiningthe exposure concentration at which a test compound is teratogenic, themethod comprising: culturing undifferentiated human stem cell-like cells(hSLCs) in a range of concentrations of the test compound and in theabsence of the test compound; determining the fold change in ornithine,or fragment, adduct, deduct or loss thereof, in the culture media ofundifferentiated hSLCs cultured in each concentration of the testcompound in comparison with hSLCs cultured in the absence of the testcompound; determining the fold change in cystine, or fragment, adduct,deduct or loss thereof, in the culture media of undifferentiated hSLCscultured in each concentration of the test compound in comparison withhSLCs cultured in the absence of the test compound; determining theratio of the fold change in ornithine, or fragment, adduct, deduct orloss thereof, to the fold change in cystine, or fragment, adduct, deductor loss thereof, for each concentration of test compound, wherein: aratio of less than or equal to about 0.88 at a given concentration ofthe test compound is indicative of the teratogenicity of the testcompound at that given concentration; and a ratio of greater than about0.88 at a given concentration of the test compound is indicative of thenon-teratogenicity of the test compound at that given concentration. 5.The method of claim 1, wherein the cystine, or fragment, adduct, deductor loss thereof, and/or ornithine, or fragment, adduct, deduct or lossthereof, are identified using a physical separation method.
 6. Themethod of claim 5, wherein the physical separation method comprises massspectrometry.
 7. The method of claim 6, wherein the mass spectrometrycomprises liquid chromatography/electrospray ionization massspectrometry.
 8. The method of claim 1, wherein the cystine, orfragment, adduct, deduct or loss thereof, and/or ornithine, or fragment,adduct, deduct or loss thereof, are measured using a colorimetric orimmunological assay.
 9. The method of claim 1, wherein the hSLCscomprise human embryonic stem cells (hESCs), human induced pluripotent(iPS) cells, or human embryoid bodies.
 10. The method of claim 1,wherein the hSLCs are cultured in a range of concentrations of the testcompound.
 11. The method of claim 10, wherein the range ofconcentrations comprises a serial dilution.
 12. The method of claim 10,wherein the range of concentrations comprises nine three-fold dilutions.13. The method of claim 10, wherein the range of concentrations isselected from about 0.04 μM to about 300 μM, about 4 μM to about 30,000μM, and about 0.0001 μM to about 10 μM.
 14. The method of claim 10,wherein the range of concentrations of the test compound comprises thetest compound's human therapeutic C_(max).
 15. The method of claim 1,wherein the hSLCs are cultured at a concentration of the test compoundcomprising the test compound's human therapeutic C_(max).
 16. The methodof claim 1, further comprising detecting one or more additionalmetabolites associated with hSLCs cultured in the presence of the testcompound in comparison with hSLCs cultured in the absence of the testcompound.
 17. The method of claim 16, wherein one or more additionalmetabolite comprises arginine, ADMA, cystathionine, and/or a fragment,adduct, deduct or loss thereof.
 18. The method of claim 1, furthercomprising determining the ratio of the fold change in arginine, orfragment, adduct, deduct or loss thereof, to the fold change in ADMA, orfragment, adduct, deduct or loss thereof, wherein: a ratio of less thanat least about 0.9 or greater than at least about 1.1 is indicative ofthe teratogenicity of the test compound; and a ratio of greater than atleast about 0.9 and less than at least about 1.1 is indicative of thenon-teratogenicity of the test compound.